📊 Upwork Jobs Database

Complete database dump of Upwork jobs with AI insights for research and analysis

🎯 What This Database Contains

This comprehensive database gives you complete access to Upwork job market data:

• 📊 1,907,883+ Job Records: Complete historical data from 2024-12-01 to 2025-09-10
• 🧠 AI-Enhanced Data: 30% of jobs include AI analysis of urgency, complexity, and requirements
• 🔍 59 Data Points: Comprehensive job details, client info, and market insights
• 📈 Market Intelligence: Perfect for research, ML training, and business analysis
• ⚡ Multiple Formats: CSV, JSON, and Parquet files for any workflow

🚀 Need Real-Time Updates?

📡 Want instant notifications and live job feeds? This database contains historical data, but if you need real-time job alerts and API access for live data streaming, check out our Upwork Jobs API & Notifications on Apify! Perfect for:

• 🔔 Instant job alerts sent to your webhook/email
• 📊 Real-time API access to the latest job postings
• 🤖 Automated job matching and filtering
• ⚡ Live data streaming for your applications

💾 Database Download

Available Formats

• 📊 CSV (3291.0 MB / 1031.0 MB.gz) - Easy to import into Excel, Google Sheets, or any spreadsheet tool
• 🔧 JSON (6457.0 MB / 1193.0 MB.gz) - Perfect for developers and API integrations
• 📄 JSONL (6177.0 MB / 1235.0 MB.gz) - Line-delimited JSON for streaming and memory-efficient processing
• ⚡ Parquet (1599.0 MB / 1364.0 MB.gz) - Optimized for big data analysis with Pandas, Spark, or BI tools
• 🗄️ SQLite (4125.0 MB / 1164.0 MB.gz) - Portable database format, works with any SQL client
• 🚀 DuckDB (3863.0 MB / 953.0 MB.gz) - High-performance analytics database with advanced SQL features

💾 Storage Recommendations

• For immediate analysis: Download uncompressed text/parquet formats
• For archival/transfer: Use compressed versions (save ~80% space)
• For SQL queries: Database formats require extraction before use
• For streaming processing: JSONL format (compressed or uncompressed)

File Information

• 📈 Total Records: ~1,907,883+ job postings
• 📅 Data Range: 2024-12-01 to 2025-09-10
• 🔄 Updated: Weekly (every Monday)

What's Included

Each record contains 59 fields including:

• Complete job details (title, description, pricing)
• Client information and hiring history
• AI-generated insights and analysis
• Timestamp and metadata

📊 Monthly Breakdown

Here's how the 1,907,883 job records are distributed by month:

2024:

• December 2024: 239,419 jobs

2025:

• January 2025: 215,727 jobs
• February 2025: 191,859 jobs
• March 2025: 236,358 jobs
• April 2025: 224,295 jobs
• May 2025: 174,768 jobs
• June 2025: 169,003 jobs
• July 2025: 193,181 jobs
• August 2025: 190,989 jobs
• September 2025: 81,206 jobs (partial month)

📋 Working Code Examples

🐍 Python Examples

CSV Format - Quick Analysis:

"""Run CSV format examples with proper error handling"""
# Load CSV efficiently with data types
df = pd.read_csv(f'{base_dir}/{base_name}.csv.gz', 
                 compression='gzip', 
                 parse_dates=['date_posted', 'created_at', 'buyer_contract_date'],
                 low_memory=False)
# Basic dataset overview
# Handle date range safely
if 'date_posted' in df.columns:
    date_posted_clean = df['date_posted'].dropna()
    if len(date_posted_clean) > 0:
# Top job categories by volume
print("\nMost popular job categories:")
if 'category_name' in df.columns:
    print(df['category_name'].value_counts().head())
# Pricing analysis
if 'price_type' in df.columns:
    hourly_jobs = df[df['price_type'] == 'Hourly']
    fixed_jobs = df[df['price_type'] == 'Fixed-price']
    if len(hourly_jobs) > 0 and 'price_min' in df.columns:
        median_hourly = hourly_jobs['price_min'].median()
        if pd.notna(median_hourly):
    if len(fixed_jobs) > 0 and 'price' in df.columns:
        median_fixed = fixed_jobs['price'].median()
        if pd.notna(median_fixed):
    if 'category_name' in df.columns and 'price_min' in df.columns:
        top_paying = df.groupby('category_name')['price_min'].median().nlargest(3).round(0)
return True

JSONL Format - Streaming Processing:

"""Run JSONL streaming examples"""
# Process JSONL line by line (memory efficient)
high_value_jobs = []
# Try compressed file first, fall back to uncompressed
jsonl_gz_path = f'{base_dir}/{base_name}.jsonl.gz'
jsonl_path = f'{base_dir}/{base_name}.jsonl'
if Path(jsonl_gz_path).exists():
    file_opener = lambda: gzip.open(jsonl_gz_path, 'rt')
elif Path(jsonl_path).exists():
    file_opener = lambda: open(jsonl_path, 'r')
else:
    return False
with file_opener() as f:
    for i, line in enumerate(f):
        if i >= 50000:  # Reasonable limit for testing
            break
        try:
            job = json.loads(line)
            # Filter for high-value opportunities
            price_min = job.get('price_min') or 0
            price = job.get('price') or 0  
            total_spent = job.get('total_spent') or 0
            # Convert string numbers to float if needed
            try:
                if isinstance(price_min, str):
                    price_min = float(price_min) if price_min not in ['', 'null', None] else 0
                if isinstance(price, str):
                    price = float(price) if price not in ['', 'null', None] else 0
                if isinstance(total_spent, str):
                    total_spent = float(total_spent) if total_spent not in ['', 'null', None] else 0
            except (ValueError, TypeError):
                continue
            if (price_min >= 50 or price >= 1000) and total_spent >= 10000:
                # Determine display price and type
                price_type = job.get('price_type', 'Unknown')
                if price_type == 'Hourly' and price_min > 0:
                    display_price = f"${price_min}/hr"
                elif price_type == 'Fixed-price' and price > 0:
                    display_price = f"${price:,.0f} fixed"
                else:
                    display_price = "Price not specified"
                high_value_jobs.append({
                    'title': job.get('title', 'No title')[:50] + ('...' if len(job.get('title', '')) > 50 else ''),
                    'category': job.get('category_name', 'Unknown'),
                    'display_price': display_price,
                    'client_spent': total_spent,
                    'url': job.get('url', 'No URL')
                })
            if len(high_value_jobs) >= 100:  # Process in batches
                break
        except (json.JSONDecodeError, KeyError, TypeError):
            continue
# Show sample results
if high_value_jobs:
    print("\nSample high-value opportunities:")
    for i, job in enumerate(high_value_jobs[:5], 1):
        print()
return True

Parquet Format - Fast Analytics:

"""Run Parquet format examples for analytics"""
# Load Parquet (fastest for analytics)
parquet_path = f'{base_dir}/{base_name}.parquet'
if not Path(parquet_path).exists():
    return False
df = pd.read_parquet(parquet_path)
parquet_file = parquet_path
# Load key business intelligence fields
selected_columns = ['title', 'category_name', 'price_type', 'price', 'price_min', 'price_max',
                   'experience_level', 'client_location', 'total_spent', 'hires', 'date_posted']
# Filter to columns that actually exist
existing_columns = [col for col in selected_columns if col in df.columns]
# Use the same file that worked above (parquet_file was set in the try/except block)
df_subset = pd.read_parquet(parquet_file, columns=existing_columns)
# Convert numeric columns to proper data types
numeric_columns = ['price', 'price_min', 'price_max', 'total_spent', 'hires']
for col in numeric_columns:
    if col in df_subset.columns:
        df_subset[col] = pd.to_numeric(df_subset[col], errors='coerce')
# Market analysis by experience level and category
if 'experience_level' in df_subset.columns and 'category_name' in df_subset.columns:
    # Prepare aggregation dictionary dynamically
    agg_dict = {}
    if 'price_min' in df_subset.columns:
        agg_dict['price_min'] = ['count', 'median']
    elif 'title' in df_subset.columns:
        agg_dict['title'] = 'count'  # Fallback to count titles
    if 'total_spent' in df_subset.columns:
        agg_dict['total_spent'] = 'median'
    if agg_dict:  # Only run if we have something to aggregate
        market_analysis = (df_subset
            .groupby(['experience_level', 'category_name'])
            .agg(agg_dict)
            .head(15))
        print("\nJob market analysis by experience level and category:")
        print(market_analysis)
    else:
        print("\nInsufficient numeric columns for market analysis")
return True

🗃️ Database Examples

SQLite - Complex Queries:

To use the SQLite database:

# Extract if compressed
gunzip upwork-jobs-2025-09-10.sqlite.gz

# Open with SQLite command line client
sqlite3 upwork-jobs-2025-09-10.sqlite

# Or open with any SQLite client (DB Browser, DataGrip, etc.)

-- SQLite - Complex Queries

-- Market opportunity analysis by category
SELECT 
    category_name,
    COUNT(*) as total_jobs,
    ROUND(AVG(price_min), 0) as avg_hourly_rate,
    ROUND(AVG(total_spent), 0) as avg_client_spending,
    COUNT(CASE WHEN experience_level = 'Expert' THEN 1 END) as expert_jobs,
    ROUND(AVG(CASE WHEN experience_level = 'Expert' THEN price_min END), 0) as expert_rate
FROM records 
WHERE price_type = 'Hourly'
    AND price_min > 0
    AND price_min IS NOT NULL
GROUP BY category_name 
HAVING total_jobs >= 100
ORDER BY avg_hourly_rate DESC 
LIMIT 15;

-- Premium clients analysis (high spending, good rates)
SELECT 
    client_location,
    COUNT(*) as jobs_posted,
    ROUND(AVG(price_min), 0) as avg_rate,
    ROUND(AVG(total_spent), 0) as avg_client_spending,
    ROUND(AVG(buyer_score), 2) as avg_rating
FROM records 
WHERE total_spent >= 10000 
    AND price_min >= 25
    AND price_type = 'Hourly'
GROUP BY client_location 
HAVING jobs_posted >= 20
ORDER BY avg_rate DESC 
LIMIT 15;

DuckDB - Advanced Analytics:

To use the DuckDB database:

# Extract if compressed
gunzip upwork-jobs-2025-09-10.duckdb.gz

# Open with DuckDB CLI
duckdb upwork-jobs-2025-09-10.duckdb

# Or connect with Python
python -c "import duckdb; conn = duckdb.connect('upwork-jobs-2025-09-10.duckdb')"

-- DuckDB - Advanced Analytics

-- Pricing distribution analysis across experience levels
SELECT 
    experience_level,
    COUNT(*) as jobs,
    ROUND(AVG(price_min), 0) as avg_rate,
    ROUND(PERCENTILE_CONT(0.5) WITHIN GROUP (ORDER BY price_min), 0) as median_rate,
    ROUND(PERCENTILE_CONT(0.75) WITHIN GROUP (ORDER BY price_min), 0) as p75_rate,
    ROUND(PERCENTILE_CONT(0.9) WITHIN GROUP (ORDER BY price_min), 0) as p90_rate
FROM records 
WHERE price_type = 'Hourly'
    AND price_min > 0
    AND price_min IS NOT NULL
GROUP BY experience_level 
ORDER BY median_rate DESC;

-- Top job categories by volume and average rates
SELECT 
    category_name,
    COUNT(*) as jobs_posted,
    ROUND(AVG(price_min), 0) as avg_hourly_rate,
    ROUND(AVG(total_spent), 0) as avg_client_spending,
    COUNT(CASE WHEN total_spent >= 10000 THEN 1 END) as established_clients
FROM records 
WHERE price_type = 'Hourly'
    AND price_min > 0
    AND price_min IS NOT NULL
GROUP BY category_name 
HAVING jobs_posted >= 100
ORDER BY jobs_posted DESC
LIMIT 15;

🚀 Quick Start Commands

# Preview data structure
head -3 upwork-jobs-2025-09-10.jsonl | jq '.'

# Count total records (fast)
zcat upwork-jobs-2025-09-10.jsonl.gz | wc -l

# Extract specific fields
zcat upwork-jobs-2025-09-10.jsonl.gz | jq -r '[.title, .category_name, .price_min] | @csv' | head

# Load in R
Rscript -e "
library(jsonlite); 
jobs <- stream_in(gzcon(file('upwork-jobs-2025-09-10.jsonl.gz', 'rb')), pagesize=1000);
cat('Loaded', nrow(jobs), 'jobs\n')
"

# Load in Excel/Google Sheets
# Use the CSV.gz file directly - most tools support gzip compression

📄 Raw JSON Samples

Here's what the actual data looks like - real records from our database:

[
{
  "id": "2096313",
  "title": "HR Officer (Talent Acquisition) | Remote",
  "description": "HR Officer (Talent Acquisition) | Remote\n\nLocation: Remote\nFull-Time retainer contract\nMUST be flexible to work across multiple timezones\n5-7 days a week as needed during busy periods. \nMust have at least 1-2 years of HR leadership, policy development and/or management experience\n\n🌍 About Shae Group\n\nShae Group is a fast-moving, AI-first company working across health, wellbeing, education, and technology. We combine human expertise with automation to build high-performing teams, products, and services worldwide. We’re growing fast, and we’re looking for a proactive HR Support Officer (Talent Acquisition & Work Performance focus) to help us recruit, onboard, and support our global team.\n\nAt Shae Group, we are a global AI-first technology and services company operating across multiple industries. Our culture is defined by high performance, rapid innovation, and values-driven leadership. When hiring, HR and managers should assess not only skills and experience, but also alignment with our way of working.\n\n1. AI-First & Future-Oriented\nWe adopt AI across every function — strategy, operations, marketing, sales, product, and client experience.\nWe hire people who are AI-savvy, adaptive, and curious about new technologies.\nCandidates should embrace experimentation, automation, and working with AI tools daily.\n\n2. Outcomes Over Effort\n- We measure success by results and KPIs, not by hours logged.\n- We are an outcomes-driven organization.\n- Employees are trusted to self-manage, deliver outcomes, and take ownership of their work.\n- HR should look for candidates with a performance-driven mindset who thrive on accountability.\n\n3. Fast, Agile & Scaling\n- Shae Group is a fast-moving, scaling organization — our pace is high, and change is constant.\n- We value people who are flexible, proactive, and comfortable with ambiguity.\n- Candidates should demonstrate resilience, problem-solving, and comfort with evolving priorities.\n\n4. Radical Transparency & Communication\n- We believe in clear, open communication and radical transparency across all levels.\n- Documentation, dashboards, and data are used to maintain alignment and accountability.\n- HR should prioritize candidates with excellent communication skills and the ability to operate confidently with executives and peers.\n\n5. Collaboration & Team Integration\n- Work is highly cross-functional — employees often collaborate across Strategy, Tech, Marketing, Sales, HR, and Product.\n- We value team players who integrate seamlessly, support colleagues, and elevate group outcomes over individual wins.\n- Hiring managers screen for collaborative attitudes, emotional intelligence, and stakeholder management skills.\n\n6. High Standards & Professionalism\n- We hold ourselves to strict quality, compliance, and delivery standards across all roles.\n- Attention to detail, accountability, and professional conduct are non-negotiable.\n- Candidates must show they can maintain quality while moving fast.\n- Our work is purpose-driven: advancing human health, wellbeing, education, and performance through precision AI.\n- Employees must resonate with the mission and values of ethical technology.\n- During interviews, HR should assess candidates’ motivation, alignment with our mission, and passion for impact.\n\n👤 Who You Are\n\n2–4+ years in Recruitment / Talent Acquisition & HR Operations.\n\n- Must be comfortable in an Ai-first organization\n- Must have skills in sourcing, screening, and coordinating interviews using Ai-optimized platforms & processes\n- Strong HR admin skills: management, onboarding, probation tracking, contracts, HRIS upkeep, policy development and implementation, ongoing engagement and performance tracking\n- Experience with HRIS/ATS tools (Workable, Breezy, Lever, Skillspot Ai etc.) and Google Workspace.\n- Organized, detail-focused, and comfortable using AI tools for drafting, scheduling, and reporting.\n- Great communicator across time zones; thrives in a remote-first environment.\n\n🎯 What You’ll Do\n\nManage recruitment pipelines: JDs, sourcing, shortlisting, interviews, offers.\nDeliver smooth onboarding & offboarding processes.\nKeep HRIS, contracts, timesheets, and policies accurate and audit-ready.\nSupport performance reviews, engagement surveys, and workforce reporting.\nUse automation + AI to streamline workflows and boost efficiency.\n\n📊 What Success Looks Like\n\nImplement 80-90% Ai-Only Systems and Processes\nFast, high-quality hires (TTF ≤ 7 days; Offer Acceptance ≥ 80%).\nSeamless onboarding (checklists completed within 5 days).\nHR records kept 99% accurate.\nInternal satisfaction ≥ 4.5/5.\n\n\n💰 Compensation\n\nUSD $1000/month for minimum 160 hours\nKPI Achievement Incentives available from USD $150 - $225/month\n\n📝 How to Apply\nPlease apply via Upwork with:\nYour resume/CV (HR + TA experience, tools used).\nA short cover letter (≤1 page) explaining how you’ll add value at Shae Group.\n\nShortlisted candidates will be invited to complete a brief skills assessment and live working session.\n\n🚀 Why Join Us?\n\nAt Shae Group, you’ll be part of a global, mission-driven team (#tech4good). You’ll get to shape an AI-enabled HR function, grow with us, and make a measurable impact.\n\nWhat's your HealthType? Let us know what yours is and we'll take your application seriously. We just need to know you've read this far ;) Get yours in under 2mins here: healthtypetest.org.\n\n🔥 Apply now to help us build a world-class HR team!",
  "date_posted": "2025-09-13T11:22:08.208Z",
  "application_requirements": null,
  "location": null,
  "price_type": "Fixed-price",
  "price": 1000,
  "price_min": null,
  "price_max": null,
  "skills": "Recruiting, Human Resource Management, Candidate Sourcing, Candidate Interviewing, Candidate Evaluation, Candidate Management",
  "experience_level": "Intermediate",
  "work_hours": null,
  "contract_to_hire": false,
  "member_since": "Sep 12, 2013",
  "client_location": "Australia",
  "local_time": "Australia/Sydney (UTC+10:00)",
  "jobs_posted": 254,
  "hire_rate": null,
  "open_jobs": 46,
  "total_spent": 248145.32,
  "hires": 171,
  "active_hires": 30,
  "avg_hourly_rate": 6.822694942707213,
  "total_hours": 25232,
  "industry": null,
  "company_size": "None",
  "created_at": "2025-09-13T11:23:16.566Z",
  "url": "https://www.upwork.com/jobs/~021966824712718789621",
  "status": "ACTIVE",
  "category_id": "531770282584862721",
  "subcategory_id": "531770282601639946",
  "category_name": "Accounting & Consulting",
  "subcategory_name": "Recruiting & Human Resources",
  "upwork_id": "021966824712718789621",
  "job_is_premium": null,
  "job_start_date": null,
  "job_delivery_date": null,
  "engagement_label": null,
  "engagement_weeks": null,
  "hourly_budget_type": null,
  "client_invites_sent": null,
  "client_last_activity": null,
  "client_positions_to_hire": 1,
  "client_total_applicants": null,
  "client_total_hired": null,
  "client_total_invited": null,
  "client_unanswered_invites": null,
  "qual_earnings": null,
  "qual_min_hours_week": null,
  "qual_min_success_score": null,
  "qual_min_hours": null,
  "qual_pref_english": "FLUENT",
  "qual_rising_talent": null,
  "qual_portfolio_required": null,
  "qual_type": "INDEPENDENT",
  "buyer_offset_utc": 36000000,
  "buyer_city": "Stones Corner",
  "buyer_feedback_count": 179,
  "buyer_score": 4.79,
  "buyer_contract_date": "2013-09-12T00:00:00.000Z",
  "buyer_payment_verified": true,
  "ai_urgency": "Moderately Urgent",
  "ai_duration": "Long-Term",
  "ai_deadline": "Flexible Deadline",
  "ai_technical_skills": "HRIS, ATS, Workable, Breezy, Lever, Skillspot Ai, Google Workspace",
  "ai_inferred_technical_skills": "AI tools, Automation, Recruitment platforms, Performance tracking",
  "ai_portfolio_requirements": null,
  "ai_specific_requirements_before_applying": "Submit resume/CV with HR + TA experience and tools used, Provide a short cover letter (≤1 page) explaining value addition",
  "ai_explicit_mention_of_agency": "No Mention",
  "ai_complexity_score": null,
  "ai_budget_estimation_indicators": null,
  "ai_clients_technical_understanding": "High",
  "ai_named_entities": "Shae Group, Workable, Breezy, Lever, Skillspot Ai, Google Workspace, healthtypetest.org",
  "ai_anti_bot_phrase": "What's your HealthType?",
  "ai_summary": "The client seeks a remote HR Officer specializing in AI-driven talent acquisition and HR operations to manage recruiting pipelines, onboarding, HRIS upkeep, and performance tracking with a final deliverable of streamlined, AI-optimized HR processes achieving specific KPIs. They expect 2–4+ years of relevant experience, strong AI and HRIS tool proficiency, flexibility across time zones, and adherence to a $1000/month budget with incentives based on performance. Watch for scope creep around demanding 5–7 days availability during busy periods and the need to consistently hit aggressive KPIs under rapid scaling; this role offers a standout chance to lead AI-enabled HR transformation in a mission-driven company."
},
{
  "id": "2073066",
  "title": "Senior AI/ML Engineer with experience DL, NLP, LLMs & CV",
  "description": "**All answers will be run through an AI screener to ensure you are answering the questions and that your are able to fill the requirements of this position. If taking the time to answer these questions is too much and if you really don't know how to do the required tasks, please do not submit a proposal. Lets not waste each others times.***\n\nLooking for a Senior AI Engineer (Full time - Independent Freelancer)\n\n*Full-time employee. if you are working on multiple projects at a time, DO NOT APPLY”\n\nPosition Overview \n\nWe are seeking a Senior AI Engineer to be the technical architect and leader of our AI-powered partnership intelligence platform. This role combines cutting-edge AI engineering with deep collaboration across our specialized team of Full Stack Data Engineer, Full Stack Backend Engineer, and Senior QA Engineer. You will be responsible for designing, building, and scaling the most advanced AI systems in the partnership space, working hand-in-hand with our engineering team to deliver unprecedented partnership success rates through intelligent automation. \n\nRole & Responsibilities \n\nAI Architecture & Technical Leadership \n\nCognitive Partner Engine Leadership: Architect and lead the development of our flagship AI system, designing sophisticated LLM-powered intelligence that processes millions of partnership data points to deliver actionable insights with unprecedented accuracy \n\nProduction AI System Design: Build enterprise-grade AI infrastructure capable of handling real-time partnership analysis, multi-modal data processing, and complex reasoning workflows using state-of-the-art transformer architectures \n\nAI Team Technical Vision: Define and drive the technical roadmap for AI capabilities, working closely with our Full Stack Data Engineer to ensure seamless data flow and with our Backend Engineer for robust API integration \n\nAdvanced Model Architecture: Design and implement custom transformer models, fine-tuning strategies, and ensemble approaches optimized for partnership intelligence and business relationship analysis \n\nLarge Language Model Excellence \n\nProduction LLM Development: Lead end-to-end LLM implementation from research to production, including fine-tuning foundation models (GPT-4, Claude, Llama) for partnership-specific use cases and domain adaptation \n\nAdvanced RAG Systems: Build sophisticated Retrieval-Augmented Generation systems that combine proprietary partnership data with LLM reasoning to deliver contextualized, accurate partnership recommendations \n\nPrompt Engineering & Optimization: Develop production-grade prompt engineering frameworks with versioning, A/B testing, and continuous optimization to ensure consistent, reliable AI outputs \n\nLLM Safety & Guardrails: Implement comprehensive AI safety measures including bias detection, content filtering, hallucination prevention, and ethical AI deployment practices \n\nAI-Data Integration & Collaboration \n\nAI-Data Pipeline Synergy: Work intimately with our Full Stack Data Engineer to design data architectures that optimize AI model training, inference, and continuous learning from partnership interactions \n\nReal-time AI Processing: Build systems that process streaming partnership data, email communications, calendar interactions, and CRM updates to provide instant AI-powered insights and recommendations \n\nFeature Engineering Leadership: Collaborate on advanced feature engineering pipelines that transform raw partnership data into AI-ready formats, ensuring optimal model performance and accuracy \n\nModel Training Infrastructure: Design and implement distributed training systems on AWS that can handle large-scale model training, fine-tuning, and continuous learning workflows \n\nProduction AI Deployment & Optimization \n\nScalable AI Inference: Build high-performance, low-latency AI inference systems capable of handling thousands of concurrent partnership analysis requests with sub-second response times \n\nModel Performance Optimization: Implement advanced optimization techniques including quantization, pruning, distillation, and efficient serving architectures to maximize performance while minimizing costs \n\nAI System Monitoring: Collaborate with our QA Engineer to establish comprehensive AI system monitoring, including model drift detection, performance degradation alerts, and quality assurance for AI outputs \n\nContinuous Model Improvement: Design automated systems for model evaluation, A/B testing, and continuous improvement based on real-world partnership outcomes and user feedback \n\nCross-functional AI Leadership \n\nEngineering Team Collaboration: Lead AI integration across our entire tech stack, ensuring our Backend Engineer can seamlessly expose AI capabilities through APIs and our QA Engineer can effectively test AI system reliability \n\nAI Strategy & Innovation: Drive AI research and development initiatives, staying at the forefront of LLM advances and implementing cutting-edge techniques in production partnership intelligence systems \n\nTechnical Mentorship: Provide AI expertise and guidance to the entire engineering team, fostering AI literacy and ensuring best practices in AI development across all systems \n\nProduct AI Integration: Partner with product and business stakeholders to translate partnership intelligence requirements into advanced AI capabilities that deliver measurable business value \n\nRequired Qualifications \n\nAdvanced AI Engineering Expertise \n\n7+ years of production software development experience with 4+ years specializing in AI/ML systems and 2+ years with production LLM deployment \n\nExpert LLM Development: Deep hands-on experience with transformer architectures, fine-tuning techniques (LoRA, QLoRA, full fine-tuning), and production deployment of models like GPT-4, Claude, Llama, or similar \n\nAdvanced RAG & Semantic Search: Proven expertise building production RAG systems, vector databases, embedding models, and semantic search capabilities for complex business applications \n\nProduction AI Architecture: Extensive experience designing and implementing scalable AI systems that handle real-time inference, model serving, and continuous learning in enterprise environments \n\nDeep Technical Foundations \n\nProgramming Excellence: Expert-level Python programming with deep knowledge of ML frameworks (PyTorch, TensorFlow), AI libraries (Hugging Face, LangChain), and production software engineering practices \n\nMachine Learning Mastery: Advanced understanding of ML algorithms, neural network architectures, optimization techniques, and mathematical foundations including linear algebra, calculus, and statistics \n\nCloud AI Infrastructure: Extensive AWS experience including SageMaker, Bedrock, Lambda, ECS for AI workloads, with hands-on knowledge of distributed training and model deployment at scale \n\nData Integration Skills: Strong experience working with data pipelines, ETL processes, and database systems to feed AI models with high-quality, real-time data \n\nAI Safety & Production Excellence \n\nAI Ethics & Safety: Deep knowledge of responsible AI development, bias detection and mitigation, AI safety practices, and implementing guardrails for production AI systems \n\nModel Optimization: Advanced skills in model compression, quantization, pruning, and inference optimization for deploying efficient, cost-effective AI systems \n\nPerformance Monitoring: Experience with MLOps practices, model monitoring, drift detection, and maintaining AI system performance in production environments \n\nA/B Testing & Evaluation: Hands-on experience with AI system evaluation, A/B testing frameworks, and measuring real-world AI impact on business metrics \n\nLeadership & Collaboration Skills \n\nTechnical Leadership: Proven experience leading AI initiatives, mentoring engineers, and driving technical decisions in fast-paced startup environments \n\nCross-functional Partnership: Exceptional collaboration skills for working with data engineers, backend engineers, QA engineers, and product teams to deliver integrated AI solutions \n\nCommunication Excellence: Outstanding ability to explain complex AI concepts to technical and non-technical stakeholders, translate business requirements into AI capabilities \n\nInnovation Drive: Track record of implementing state-of-the-art AI research in production, staying current with latest developments, and driving innovation in AI applications \n\nPreferred Qualifications \n\nAdvanced AI Specialization \n\nPh.D./Master's in AI/ML: Advanced degree in Computer Science, Machine Learning, AI, or related field with focus on practical AI system development \n\nMulti-modal AI Systems: Experience building AI systems that process text, structured data, and other modalities simultaneously for comprehensive business intelligence \n\nReinforcement Learning: Knowledge of RLHF, reinforcement learning techniques, and training AI systems to optimize for business outcomes rather than just accuracy \n\nAI Research Background: Experience with AI research, publications, open-source contributions, or implementing cutting-edge research in production systems \n\nDomain & Industry Expertise \n\nPartnership Intelligence: Understanding of partnership management, business relationship dynamics, and experience building AI systems for B2B or relationship-focused applications \n\nEnterprise AI Deployment: Experience with enterprise-scale AI deployments, handling complex integration requirements, security concerns, and regulatory compliance \n\nStartup AI Leadership: Experience building AI systems from scratch in startup environments, balancing innovation with practical business constraints and rapid iteration \n\nAdvanced Technical Skills \n\nDistributed AI Systems: Experience with distributed 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\n\nModel Serving: Custom inference servers, batching systems, and low-latency API endpoints \n\nMonitoring: Comprehensive AI system monitoring, drift detection, and performance analytics \n\nMLOps: Model versioning, experiment tracking, automated retraining, and deployment pipelines \n\nData Integration & Collaboration \n\nData Pipeline Integration: Seamless connection with our Full Stack Data Engineer's ETL systems and real-time data streams \n\nAPI Integration: Close collaboration with Backend Engineer for exposing AI capabilities through robust, scalable APIs \n\nQuality Assurance: Partnership with QA Engineer for comprehensive AI system testing, validation, and reliability assurance \n\nAnalytics Integration: Connection with PostHog, Mixpanel, Grafana for AI performance and business impact monitoring \n\nTeam Collaboration Structure \n\nAI-Data Engineering Partnership \n\nDaily technical alignment with Full Stack Data Engineer on data pipeline optimization, feature engineering, and real-time data processing for AI models \n\nJoint architecture decisions on data schemas, storage optimization, and analytics integration that support both AI inference and business intelligence \n\nCollaborative model training including data quality assurance, feature validation, and continuous learning system design \n\nAI-Backend Integration \n\nSeamless API development with Full Stack Backend Engineer to expose AI capabilities through Next.js/NestJS applications \n\nPerformance optimization collaboration ensuring AI inference integrates efficiently with application workflows and third-party integrations \n\nJoint system architecture for handling AI workloads alongside traditional backend processing and database operations \n\nAI-QA Excellence \n\nComprehensive AI testing strategy developed with Senior QA Engineer, including model output validation, bias testing, and system reliability assurance \n\nJoint quality frameworks for AI-specific testing approaches, automated validation, and continuous monitoring of AI system performance \n\nCollaborative debugging and optimization of AI systems based on quality metrics and production performance analysis",
  "date_posted": "2025-09-09T21:17:32.268Z",
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  "price_type": "Hourly",
  "price": null,
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  "skills": "Artificial Intelligence, TensorFlow, Machine Learning, Deep Learning, Python, Artificial Neural Network, Neural Network, Natural Language Processing, AI Development, AI Model Integration, LangChain, AI Agent Development, Full-Stack Development, NestJS, AI App Development",
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  "buyer_offset_utc": -25200000,
  "buyer_city": "San Francisco",
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  "buyer_contract_date": "2025-06-06T00:00:00.000Z",
  "buyer_payment_verified": true,
  "ai_urgency": "Not Urgent",
  "ai_duration": "Long-Term",
  "ai_deadline": "No Deadline",
  "ai_technical_skills": "Deep Learning, Natural Language Processing, Large Language Models, Computer Vision, Python, PyTorch, TensorFlow, Hugging Face, LangChain, AWS SageMaker, AWS Bedrock, AWS Lambda, AWS ECS, Distributed Training, Model Fine-tuning, Prompt Engineering, RAG Systems, Semantic Search, Model Optimization, MLOps, A/B Testing",
  "ai_inferred_technical_skills": "API Development, Data Engineering, Feature Engineering, Model Monitoring, Cloud Infrastructure, Model Serving, Quality Assurance, Reinforcement Learning, Vector Databases, Experiment Tracking",
  "ai_portfolio_requirements": null,
  "ai_specific_requirements_before_applying": "Answer AI screener questions to demonstrate ability to fulfill position requirements, Do not apply if working on multiple projects simultaneously",
  "ai_explicit_mention_of_agency": "No Agencies",
  "ai_complexity_score": null,
  "ai_budget_estimation_indicators": null,
  "ai_clients_technical_understanding": "Expert",
  "ai_named_entities": "GPT-4, Claude, Llama, LoRA, QLoRA, PyTorch, TensorFlow, Hugging Face, LangChain, LlamaIndex, Pinecone, Weaviate, Chroma, AWS SageMaker, AWS Bedrock, AWS Lambda, AWS ECS, Next.js, NestJS, PostHog, Mixpanel, Grafana",
  "ai_anti_bot_phrase": "If taking the time to answer these questions is too much and if you really don't know how to do the required tasks, please do not submit a proposal.",
  "ai_summary": "You’ll architect, lead, and deploy a full-scale AI platform leveraging cutting-edge LLMs and AI infrastructure to deliver real-time partnership intelligence with strong cross-team collaboration; the end product is a production-ready, scalable AI system integrated with data and backend pipelines. The client demands a senior engineer with 7+ years experience, deep expertise in LLM fine-tuning, production AI systems, AWS deployment, and AI safety, working full-time without multitasking on other projects. Watch for the strict no-multitasking policy and heavy emphasis on technical leadership and collaboration, which signals a high-expectation startup environment requiring proactive communication and ownership."
},
{
  "id": "2047200",
  "title": "Full Website Redesign & Development for a Medical Device Reprocessing Provider (with Geo-Redirect)",
  "description": "Complete Website Overhaul – Built from Scratch (No Existing Assets)\n\nWho We Are and What We Need\n\nWe’re a leading company in medical device reprocessing, working with hospitals and healthcare facilities to ensure surgical and endoscopic equipment is sterilized to the highest standards. Our work helps healthcare providers stay compliant and efficient, and we operate across the U.S., Canada, and beyond.\n\nOur current website isn’t cutting it—it doesn’t reflect who we are or what we do. So, we’re starting fresh with a brand-new site, built from the ground up with no reliance on existing content, designs, or images. We need a modern, professional website that’s easy to navigate, packed with clear information, and designed for healthcare decision-makers like administrators and procurement teams.\n\nWe’re looking for a talented web development team to take this on—someone who can create original content, design custom visuals, build a simple geo-routing system, add an AI chatbot, and integrate a CRM. This proposal lays out everything we need so you can review it, provide a quote, and let us know how you’d bring this to life.\n\nTo make sure you’ve read this carefully, please start your proposal with the phrase: “Crispy croissants are the best.” If you don’t, we’ll assume you skimmed it and move on.\n\nAbout Us and the Project\nWe specialize in reprocessing medical devices, ensuring surgical and endoscopic tools meet strict regulatory standards. Our facilities and logistics support clients in the U.S., Canada, and international markets, backed by ISO certifications that prove our commitment to quality. Our current website doesn’t tell this story well, so we’re scrapping it entirely—no tweaks, no redesign, just a clean slate.\n\nHere’s what we’re after:\n•\tA sharp, professional website that’s easy to use and looks great on any device.\n•\tA design that follows top-notch UI/UX practices, making it simple for our audience to find what they need.\n•\tFresh content, including text and custom infographics, to explain our services clearly and visually.\n•\tA geo-routing system that directs users to the right regional content (U.S., Canada, or international) based on their location, with an option to switch regions manually.\n•\tAn AI chatbot to engage visitors, answer questions, and capture leads.\n•\tIntegration with a CRM (Zoho or Salesforce) to manage those leads and keep our sales team organized.\n•\tA CMS that lets our team update content without needing a developer on speed dial.\n•\tFast load times and SEO optimization to ensure the site performs well and ranks high.\nOur audience—healthcare administrators, procurement folks, and regulatory professionals—needs clear, concise info without fluff. We want a site that feels high-end but doesn’t overwhelm with complexity.\n\nWhat We Expect from You\nHere’s a breakdown of the key pieces we need delivered:\n1. Complete Website Build\n•\tCreate a brand-new site with a clean, modern look—no reusing old assets.\n•\tOrganize the content so it’s easy to follow, focusing on information over flashy marketing.\n•\tMake it fully responsive for phones, tablets, and desktops, and test it across major browsers (Chrome, Firefox, Safari, Edge).\n•\tKeep performance snappy (aim for under 3 seconds to load) and meet accessibility standards like WCAG 2.1.\n\n2. Original Content and Infographics\n•\tWrite clear, professional content from scratch, covering:\no\tOur company’s story, mission, and expertise in medical device reprocessing.\no\tDetails on our sterilization services and processes.\no\tInfo about our facilities, locations, logistics, and ISO certifications.\n•\tDesign custom infographics to break down complex ideas (like our sterilization process) into visuals that are easy to understand.\n•\tKeep all content concise, professional, and tailored to healthcare pros.\n\n3. Geo-Routing and Navigation\n•\tSet up a system to automatically send users to the right regional content based on their IP:\no\tU.S. visitors get U.S.-specific services and navigation.\no\tCanadian visitors see Canada-specific info.\no\tInternational visitors land on a general corporate page.\n•\tAdd a simple way for users to switch regions manually (like a dropdown menu).\n•\tEnsure the transitions are smooth and don’t disrupt the user experience.\n\n4. AI Chatbot\n•\tBuild an AI chatbot to engage visitors and provide info, with these features:\no\tWhat It Covers:\n\tOur company background, expertise, and services.\n\tDetails on facilities, locations, logistics, and ISO certifications.\no\tHow It Works:\n\tText-based chats for quick, typed questions and answers.\n\tSpeech-to-text option for voice queries to make it accessible (text or voice responses are fine).\no\tWhat It Doesაშ:\n\tCaptures leads by guiding users to forms, consultation requests, or resource downloads.\n\tDirects users to the right pages (like regional service pages) based on their questions or location.\n\tStarts conversations with prompts like, “Need help with sterilization solutions?” to keep users engaged.\no\tTech Details:\n\tUse natural language processing to handle varied questions intelligently.\n\tTie it to the geo-routing system for region-specific responses.\n\tEnsure it’s mobile-friendly and fits the site’s clean, professional vibe.\n\tFollow healthcare privacy rules (like HIPAA) for any data collection.\n\n5. CRM Integration\n•\tConnect the site to either Zoho or Salesforce for lead management:\no\tLead Capture: Grab user info (name, email, region, etc.) from chatbot chats, forms, or other interactions.\no\tOrganization: Tag leads by region and interest for targeted follow-ups.\no\tAutomation: Set up workflows like assigning leads to sales reps or sending follow-up emails.\no\tAnalytics: Track user actions (like pages visited or chatbot queries) to guide our sales team.\n•\tEnsure secure data handling that complies with healthcare regulations (e.g., GDPR, HIPAA).\n•\tMake sure the CRM works smoothly with the CMS so our team can access data easily.\n\n6. SEO and Performance\n•\tOptimize the site for search engines with:\no\tProper metadata (titles, descriptions, keywords).\no\tClean, user-friendly URLs.\no\tStructured data for better search visibility.\n•\tKeep the site fast with techniques like image compression and minified code.\n•\tDesign it mobile-first to ensure a great experience on all devices.\n\n7. CMS and Support\n•\tUse a CMS (like WordPress or Webflow) that lets our team update text and images without coding skills.\n•\tProvide a quick training session and documentation for the CMS and CRM.\n•\tOffer 30 days of post-launch support to fix bugs or make minor tweaks.\n\nWho We’re Looking For\nWe want a team that brings the right skills and reliability to the table:\n• Full Website Builds: You’ve built sites from scratch before, with a portfolio of clean, professional designs.\n• B2B or Healthcare Experience: Bonus points if you’ve worked with healthcare or technical businesses and understand their audiences.\n•\tVisual Storytelling: You can turn complex ideas into clear infographics and content.\n•\tTechnical Know-How: You’re skilled in SEO, performance optimization, geo-routing, and secure \nCRM integrations.\n•\tChatbot Expertise: You’ve built AI chatbots with text and voice capabilities.\n•\tDependability: You hit deadlines and keep us in the loop. Ghosting is a non-starter.\n•\tCompliance: You understand healthcare regulations like HIPAA and can ensure the site meets them.\nTimeline and Budget\n•\tTimeline: We need the site finished in8–10 weeks, from kickoff to launch, including design, content, testing, and go-live.\n•\tBudget: Send us a detailed quote breaking down costs for design, development, content, chatbot, CRM, and support. Include any extra costs for tools, plugins, or services (like hosting or CMS licenses).\n•\tSchedule: Provide a rough timeline with key milestones \n\nHow to Apply\nPlease submit a proposal that includes:\n1.\tCompany Background: A quick intro to your team and experience with full-site builds, especially in B2B or healthcare.\n2.\tPortfolio: Links to 3–5 relevant projects showing your design and technical skills.\n3.\tApproach:\na.\tWhat CMS would you use, and why is it the best fit?\nb.\tHow will you handle geo-routing and regional navigation?\nc.\tHow will you create content and infographics for our industry?\nd.\tWhat’s your plan for the AI chatbot, including platform and integration?\ne.\tHow will you integrate Zoho or Salesforce securely?\nf.\tWhat’s your approach to SEO and performance optimization?\n4.\tTimeline: A breakdown of your project phases and milestones.\n5.\tBudget: A clear cost estimate, including any additional fees (e.g., plugins, licenses).\n6.\tTeam and Communication: Who’s on your team, their roles, your time zone, and how you’ll keep us updated.\n\nReminder: Start your proposal with “Crispy croissants are the best” to show you’ve read this carefully. Proposals without this phrase won’t be considered.\n\nHow We’ll Choose\nWe’ll evaluate proposals based on:\n•\tHow well you meet our requirements.\n•\tYour experience with similar projects.\n•\tRealistic timeline and clear process.\n•\tCompetitive, transparent pricing.\n•\tRelevant healthcare or B2B portfolio.\n•\tQuality of design and user-focused solutions.\n\nFinal Thoughts\nThis isn’t just about building a pretty website—it’s about creating a tool that helps healthcare professionals trust and engage with our business. We need a partner who gets that and can deliver a site that’s functional, compliant, and impressive. We’re excited to hear your ideas and see how you can bring this project to life.\n\nDon’t forget to start your proposal with “Crispy croissants are the best.” Looking forward to your response!",
  "date_posted": "2025-09-05T13:59:41.829Z",
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  "price_type": "Fixed-price",
  "price": 1000,
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  "skills": "Web Design, AI Chatbot, Zoho CRM, Mockup, User Flow, Website, Custom Web Design, Sales Funnel, Journey Mapping, Search Engine Optimization, All in One SEO, Landing Page, Style Guide, JavaScript, CSS, HTML",
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  "buyer_offset_utc": -10800000,
  "buyer_city": "Mississauga",
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  "buyer_contract_date": "2010-02-09T15:28:08.000Z",
  "buyer_payment_verified": true,
  "ai_urgency": "Moderately Urgent",
  "ai_duration": "Mid-Term",
  "ai_deadline": "Fixed Deadline",
  "ai_technical_skills": "Web Development, UI/UX Design, Content Creation, Infographic Design, Geo-Routing, AI Chatbot Development, CRM Integration, SEO, Performance Optimization, CMS (WordPress or Webflow), Accessibility (WCAG 2.1), HIPAA Compliance, GDPR Compliance",
  "ai_inferred_technical_skills": "JavaScript, HTML, CSS, Natural Language Processing, Voice Recognition, Lead Management, Cross-Browser Testing",
  "ai_portfolio_requirements": null,
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  "ai_budget_estimation_indicators": null,
  "ai_clients_technical_understanding": "Moderate",
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  "ai_anti_bot_phrase": "Crispy croissants are the best",
  "ai_summary": "Build a completely new, responsive website from scratch for a medical device reprocessing firm, including original content, infographics, geo-routing by region, an AI chatbot with text and voice, and CRM integration, all optimized for SEO and performance. The client expects a healthcare-experienced team delivering within 8-10 weeks, with clear proposals starting “Crispy croissants are the best,” detailed quotes covering design through support, and adherence to HIPAA and similar regulations. Watch for scope creep from extensive chatbot and CRM features, compliance demands, and a strict callout phrase signaling attentiveness—a strong opportunity for agencies skilled in complex, compliant healthcare platforms."
},
{
  "id": "2095444",
  "title": "Vision AI Data Scientist",
  "description": "Thalmaar is seeking an innovative Data Scientist with deep expertise in Large Language Models and hands-on experience with hardware integration. In this role, you'll bridge the gap between cutting-edge AI algorithms and physical hardware systems, developing intelligent solutions that combine LLM capabilities with sensor and camera technologies. 3 month pilot run will be done to see how good the candidate is before bringing the resource fulltime onboard. Please apply only if you are fine with that. \n\nKey Responsibilities\nDesign, develop, and deploy LLM-based solutions integrated with hardware sensors and camera systems. \nImplement and optimize Vision AI models for real-time processing of camera data streams. \nCollaborate with hardware engineering teams to develop AI-driven solutions for customer applications\nConduct research and experimentation with multimodal AI systems combining visual, textual, and sensor data\nDevelop APIs and integration frameworks for seamless hardware-AI communication\nPerform data analysis and feature engineering from diverse hardware data sources\n\nRequired Qualifications\n3+ years professional experience with Large Language Models (GPT, BERT, Llama, or similar)\nStrong background in Python and machine learning frameworks (PyTorch, TensorFlow, Hugging Face)\nHands-on experience with hardware integration (sensors, cameras, IoT devices, embedded systems)\nExperience with computer vision and image processing techniques\nProficiency in API development and cloud deployment (AWS, Azure, GCP)\nSolid understanding of data preprocessing and feature extraction from hardware data streams\n\nWrite Aloha Thalmaar at the top so I know you are not posting canned messages.",
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  "buyer_contract_date": "2022-03-29T00:00:00.000Z",
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  "ai_urgency": "Moderately Urgent",
  "ai_duration": "Short-Term",
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  "ai_technical_skills": "Large Language Models, Python, PyTorch, TensorFlow, Hugging Face, Hardware Integration, Computer Vision, Image Processing, API Development, Cloud Deployment",
  "ai_inferred_technical_skills": "Machine Learning, Data Analysis, Feature Engineering, Embedded Systems, IoT",
  "ai_portfolio_requirements": null,
  "ai_specific_requirements_before_applying": "Write Aloha Thalmaar at the top",
  "ai_explicit_mention_of_agency": "No Mention",
  "ai_complexity_score": null,
  "ai_budget_estimation_indicators": null,
  "ai_clients_technical_understanding": "High",
  "ai_named_entities": "Thalmaar, GPT, BERT, Llama, PyTorch, TensorFlow, Hugging Face, AWS, Azure, GCP",
  "ai_anti_bot_phrase": "Write Aloha Thalmaar at the top",
  "ai_summary": "Aloha Thalmaar, you need a data scientist to develop and deploy Large Language Model solutions integrated with hardware sensors and camera systems, delivering a functional pilot within three months. The ideal candidate must have 3+ years in LLMs, hands-on hardware integration experience, expertise in Python and AI frameworks, and be comfortable with the trial period before full-time hiring. Watch for potential scope creep as the role spans AI research, hardware collaboration, API development, and cloud deployment, but this also offers a unique chance to work on cutting-edge multimodal AI systems combining vision and language."
},
{
  "id": "2095193",
  "title": "E-commerce Manager for TikTok Shop & Shopify Growth",
  "description": "🚨🚨🚨🚨🚨 IMPORTANT — PLEASE READ BEFORE APPLYING 🚨🚨🚨🚨🚨\n\nBefore you send a proposal, carefully read everything below.\nIf you do not cover all or most of the listed responsibilities, please do not apply.\n\nThis list is the foundation of how I see my manager and the minimum requirements for this role.\nIf you also bring additional skills or knowledge beyond what is written here, that will be considered a strong plus.\n\n\n-- Role Description\n\nI’m looking for an experienced e-commerce manager to take full ownership of developing two stores — TikTok Shop and Shopify. Both stores are new, so I need someone who can:\n\nlaunch everything from zero to first sales,\nbuild a sustainable growth strategy,\nrapidly test and scale trending products.\n\n-- Key Responsibilities\n\nMarketplaces End-to-End\nFull setup of TikTok Shop and Shopify: design, structure, payment systems, return policy, logistics.\nIntegration of Shopify products into TikTok Shop for seamless selling on both platforms.\nTrend Research & Product Sourcing\nUse AI tools and third-party services (Pipiads, Minea, Dropship IO, Amazon Movers & Shakers, etc.) to find top-selling products and content ideas.\nSource and test trending products with guaranteed fast delivery (CJ Dropshipping, Zendrop, AutoDS).\nNegotiate with suppliers to reduce costs and accelerate logistics.\nVideo Content Creation and Management\nDevelop a creative content strategy (TikTok, Instagram Reels, YouTube Shorts, Facebook Reels).\nCreate scripts, select trending audio, edit videos, add subtitles and watermarks.\nUse AI tools for video generation, automatic subtitles, music, and voiceovers.\nPublish and optimize content daily according to each platform’s algorithms.\nInfluencer and Creator Marketing\nIdentify, select, and negotiate with suitable influencers and creators.\nOrganize product sample shipments, track deliveries, and gather feedback.\nNegotiate collaboration terms (barter/paid, KPIs for reach and sales).\nMonitor campaign performance and provide ROI reports.\nMarketing and Sales Growth\nLaunch and manage paid advertising (Spark Ads, TikTok Ads, Meta Ads).\nBuild sales funnels, set up retargeting and A/B tests.\nWork with analytics: GMV, ROI, net profit, CAC (customer acquisition cost).\nApply AI services for trend forecasting and data analysis.\nTeam Management and Outsourcing\nAssign tasks to freelancers (video editors, designers, copywriters) and monitor deadlines.\nHire additional contractors (e.g., photographers, content creators) when needed.\nCreate clear instructions and scalable processes to delegate and expand tasks efficiently.\nOptimization and Automation\nImplement AI tools for automation: autoposting, sales analytics, automated reporting.\nContinuously optimize campaigns and store performance.\nFinancial Planning and Reporting\nForecast budgets for advertising, content, and inventory.\nPrepare reports: brief daily updates and detailed weekly reports on sales, ads, and profits.\nPlan the timeline for reaching break-even and growing net profit.\n\n-- Required Competencies\n\nDeep understanding of TikTok algorithms and Shopify mechanics (SEO, checkout, upsell, pixel).\nProven experience launching new products from idea to stable sales.\nKnowledge of influencer and affiliate marketing.\nProficiency with modern AI tools for trend discovery, content creation, and automation.\nStrong organizational skills, discipline, and ability to meet deadlines.\n\n-- What I Want to See in Your Reply\n\nAbout you and your experience: real case studies with numbers (GMV growth, profit, successful launches).\nStep-by-step plan for the first 1–2 months, including:\nwhat will be done in week one, month one, and month two;\napproximate ad and inventory budget (starting with $2K–$5K).\n\n--Financial projections:\n\nprojected GMV (pessimistic / realistic / optimistic),\ngross revenue, net profit, and break-even timeline.\nService pricing: a fair starting rate considering the store is new.\nAutomation proposals: which AI, services, and partner platforms you would connect to accelerate sales.\n\n-- We Offer\n\nFlexible cooperation model (fixed fee + percentage of sales).\nFast communication and support for smooth project launches.\nOpportunity for long-term work and brand scaling.\n\n--- Your task as a candidate is to demonstrate strategic thinking and real experience. The more detailed your plan, budgets, and forecasts, the higher the chance of collaboration.",
  "date_posted": "2025-09-13T04:20:12.120Z",
  "application_requirements": null,
  "location": null,
  "price_type": "Hourly",
  "price": null,
  "price_min": null,
  "price_max": null,
  "skills": "Shopify, Social Media Marketing, Instagram, Social Media Management",
  "experience_level": "Intermediate",
  "work_hours": "More than 30 hrs/week",
  "contract_to_hire": false,
  "member_since": "Jul 19, 2025",
  "client_location": "USA",
  "local_time": "America/Chicago (UTC-05:00)",
  "jobs_posted": 1,
  "hire_rate": null,
  "open_jobs": 1,
  "total_spent": null,
  "hires": 1,
  "active_hires": null,
  "avg_hourly_rate": null,
  "total_hours": null,
  "industry": null,
  "company_size": "None",
  "created_at": "2025-09-13T04:21:20.466Z",
  "url": "https://www.upwork.com/jobs/~021966718529353821173",
  "status": "ACTIVE",
  "category_id": "531770282580668418",
  "subcategory_id": "531770282589057026",
  "category_name": "Web, Mobile & Software Dev",
  "subcategory_name": "Ecommerce Development",
  "upwork_id": "021966718529353821173",
  "job_is_premium": null,
  "job_start_date": null,
  "job_delivery_date": null,
  "engagement_label": "1 to 3 months",
  "engagement_weeks": 9,
  "hourly_budget_type": "FULL_TIME",
  "client_invites_sent": null,
  "client_last_activity": null,
  "client_positions_to_hire": 1,
  "client_total_applicants": null,
  "client_total_hired": null,
  "client_total_invited": null,
  "client_unanswered_invites": null,
  "qual_earnings": null,
  "qual_min_hours_week": 40,
  "qual_min_success_score": null,
  "qual_min_hours": null,
  "qual_pref_english": "ANY",
  "qual_rising_talent": null,
  "qual_portfolio_required": null,
  "qual_type": "ANY",
  "buyer_offset_utc": -18000000,
  "buyer_city": "Fort Pierce",
  "buyer_feedback_count": null,
  "buyer_score": null,
  "buyer_contract_date": "2025-07-19T00:00:00.000Z",
  "buyer_payment_verified": true,
  "ai_urgency": "Moderately Urgent",
  "ai_duration": "Long-Term",
  "ai_deadline": "Flexible Deadline",
  "ai_technical_skills": "TikTok Shop, Shopify, SEO, checkout, upsell, pixel, influencer marketing, affiliate marketing, AI tools, paid advertising, Spark Ads, TikTok Ads, Meta Ads, sales funnels, retargeting, A/B testing, analytics, financial planning",
  "ai_inferred_technical_skills": "video editing, content creation, social media marketing, supplier negotiation, logistics management, automation, reporting",
  "ai_portfolio_requirements": null,
  "ai_specific_requirements_before_applying": "Provide real case studies with numbers (GMV growth, profit, successful launches), Submit a step-by-step plan for the first 1–2 months including weekly and monthly milestones, Include approximate ad and inventory budget (starting with $2K–$5K), Provide financial projections: projected GMV (pessimistic / realistic / optimistic), gross revenue, net profit, and break-even timeline, Propose automation tools and partner platforms to accelerate sales, Offer service pricing considering the store is new",
  "ai_explicit_mention_of_agency": "No Mention",
  "ai_complexity_score": null,
  "ai_budget_estimation_indicators": null,
  "ai_clients_technical_understanding": "High",
  "ai_named_entities": "TikTok Shop, Shopify, Pipiads, Minea, Dropship IO, Amazon Movers & Shakers, CJ Dropshipping, Zendrop, AutoDS, TikTok, Instagram Reels, YouTube Shorts, Facebook Reels, Spark Ads, TikTok Ads, Meta Ads",
  "ai_anti_bot_phrase": "🚨🚨🚨🚨🚨 IMPORTANT — PLEASE READ BEFORE APPLYING 🚨🚨🚨🚨🚨",
  "ai_summary": "The client needs an experienced e-commerce manager to fully set up and launch two new stores on TikTok Shop and Shopify, delivering initial sales and scalable growth with product sourcing, marketing, automation, and team management. They expect proven track records with measurable results, a detailed phased plan for the first two months, budget forecasts starting around $2K–$5K, and expertise in AI tools, TikTok algorithm, and influencer marketing for rapid scaling. Watch for scope creep in the broad responsibilities spanning marketplaces, content, ads, and outsourcing, but there’s a strong opportunity for long-term collaboration and revenue sharing."
}
]

📋 Complete Field Reference

All 59 available fields with descriptions and example values:

Essential Job Information

• Job Title (title) - text: The job posting title as written by the client. Contains the main description of what work needs to be done. Examples: Build a React Dashboard with Real-time Analytics, Virtual Assistant for Email Management, Logo Design for Tech Startup

• Description (description) - text: Full job description text as written by the client. Contains detailed requirements, expectations, and project scope. Examples: We need an experienced React developer to build a ..., Looking for a Python expert who can integrate machine learning models ...

• Skills (skills) - text: Comma-separated list of required skills and technologies for the job as specified by the client. Examples: JavaScript, React, Node.js, Python, Machine Learning, TensorFlow

• Price Type (price_type) - select: How the job is priced: Fixed Price (one-time payment) or Hourly (paid per hour worked). Examples: Fixed-price, Hourly

• Budget/Price - Fixed-price (price) - numeric: The budget amount for the fixed-price job. Examples: 500, 1200, 50

• Hourly Rate - Min (price_min) - numeric: Minimum budget or hourly rate for the job. Lower bound of the client's budget range. Examples: 25, 50, 100

• Hourly Rate - Max (price_max) - numeric: Maximum budget or hourly rate for the job. Upper bound of the client's budget range. Examples: 75, 150, 500

• Category Name (category_name) - select: Main category of the job (e.g., Web Development, Data Science, Design). Upwork's primary job classification. Examples: Accounting & Consulting, Admin Support, Customer Service

• Subcategory Name (subcategory_name) - select: Specific subcategory within the main category (e.g., Front-End Development, Machine Learning). More granular classification. Examples: 3D Modeling & CAD, Accounting & Bookkeeping, AI Apps & Integration

• Date Posted (date_posted) - date: When the job was posted on Upwork. Use this to find recent opportunities or analyze posting patterns. Examples: 2024-01-15, 2024-01-20T14:30:00Z

• Url (url) - text: Direct link to the job posting on Upwork. Use this to view the full job details or apply. Examples: https://www.upwork.com/jobs/~01234567890abcdef, https://www.upwork.com/jobs/~987654321fedcba09

• Keywords Search (keywords) - text: Full-text search across job title, description, skills, categories, location, industry, and AI-generated fields. Uses PostgreSQL full-text search for fast performance on millions of jobs. Examples: python machine learning, react javascript typescript, design ui ux figma

• Exclude Keywords (exclude_keywords) - text: Exclude jobs containing any of these keywords. Uses the same full-text search across job title, description, skills, categories, location, industry, and AI-generated fields. Perfect for filtering out unwanted job types or technologies. Examples: wordpress php, data entry copy paste, logo design graphic

Job Requirements

• Experience Level (experience_level) - select: Required experience level for the job: Entry Level, Intermediate, or Expert. Examples: Entry Level, Intermediate, Expert

• Contract To Hire (contract_to_hire) - boolean: Whether the job has potential to convert from contract to permanent employment. Examples: True, False

• Engagement Label (engagement_label) - select: Expected duration or type of engagement (e.g., 1 to 3 months, 3 to 6 months, Less than 1 month, Less than 1 week, More than 6 months). Examples: 1 to 3 months, 3 to 6 months, Less than 1 month

• Engagement Weeks (engagement_weeks) - select: Project duration in weeks. Options: 1, 3, 9, 18, 52 weeks. Examples: 1, 3, 9

• Qual Min Hours Week (qual_min_hours_week) - select: Minimum hours per week required for hourly jobs. Options: 10, 30, 40. Examples: 10, 30, 40

• Qual Min Success Score (qual_min_success_score) - select: Minimum Upwork success score required to apply for the job. Examples: 50, 80, 90

• Qual Pref English (qual_pref_english) - select: Client's preferred English proficiency level for freelancers. Examples: ANY, CONVERSATIONAL, FLUENT

• Qual Rising Talent (qual_rising_talent) - boolean: Whether the job is open to Upwork Rising Talent (newer freelancers with potential). Examples: True, False

• Qual Portfolio Required (qual_portfolio_required) - boolean: Whether the client requires a portfolio or work samples to apply. Examples: True, False

• Qual Type (qual_type) - select: Type of freelancer the client is looking for: Agency (team/company), Independent (solo freelancer), or Any (no preference). Examples: AGENCY, ANY, INDEPENDENT

Client Information

• Client Location (client_location) - select: Geographic location of the client posting the job. Examples: United States, United Kingdom, Canada

• Jobs Posted (jobs_posted) - numeric: Total number of jobs the client has posted on Upwork. Examples: 1, 10, >50

• Client Hire Rate (hire_rate) - numeric: Percentage of freelancers the client has hired from total applications. Higher rates indicate clients who actively hire rather than just browse. Examples: 75, 90, 50

• Client Avg Hourly Rate (avg_hourly_rate) - numeric: Average hourly rate this client typically pays freelancers. Based on their historical hiring patterns. Examples: 45.50, 75.00, >=100

• Open Jobs (open_jobs) - numeric: Number of jobs the client currently has open/active. Examples: 0, 2, <5

• Total Spent (total_spent) - numeric: Total amount the client has spent on Upwork across all their projects. Examples: 100, 500, >=1000000

• Hires (hires) - numeric: Total number of freelancers hired by the client. Examples: 1, 10, >50

• Active Hires (active_hires) - numeric: Number of freelancers currently hired by the client. Examples: 1, 10, >50

• Total Hours (total_hours) - numeric: Total number of hours the client has worked on Upwork across all their projects. Examples: 100, 500, >=1000

• Industry (industry) - select: Main industry the client operates in. Select from available choices. Examples: Aerospace, Agriculture & Forestry, Art & Design

• Company Size (company_size) - numeric: Size of the client's company. Predefined option for company size. Select from available choices. Examples: 0, 1, 10

• Buyer City (buyer_city) - select: City where the client is located. Examples: New York, London, Paris

• Buyer Feedback Count (buyer_feedback_count) - numeric: Number of feedbacks the client has received. Examples: 1, 10, >=2

• Buyer Score (buyer_score) - numeric: Score of the client's performance on Upwork. Examples: >=4.7, 5.0

• Buyer Contract Date (buyer_contract_date) - date: Date when the client first registered their account on Upwork. Indicates how long the client has been active on the platform. Examples: 2024-01-15, 2024-01-20T14:30:00Z

• Buyer Payment Verified (buyer_payment_verified) - boolean: Boolean flag indicating whether the client has verified their payment method on Upwork. Examples: True, False

AI-Powered Insights

• Urgency (ai_urgency) - select: AI-detected urgency level of the job based on language and posting patterns. Examples: Critical, Fixed Deadline, Immediate

• Duration (ai_duration) - select: AI-detected project duration based on job description analysis. Indicates expected length and type of engagement. Examples: Long-Term, Project-Based, Short-Term

• Deadline (ai_deadline) - select: AI-detected deadline type for the job based on urgency indicators and time-sensitive language in the job description. Examples: Fixed Deadline, Flexible Deadline, Immediate Deadline

• Technical Skills (AI Extracted) (ai_technical_skills) - text: Technical skills explicitly mentioned in the job description, extracted using AI. These are skills directly stated by the client as requirements or preferences. Examples: JavaScript, React, Node.js, Python, Django, PostgreSQL, AWS, Docker, Kubernetes

• Technical Skills (AI Inferred) (ai_inferred_technical_skills) - text: Technical skills inferred by AI from the job description context, even when not explicitly mentioned. These are skills likely needed based on project requirements and industry patterns. Examples: Git, REST APIs, Testing, Database Design, Security, Responsive Design, SEO

• Portfolio Requirements (ai_portfolio_requirements) - select: AI-detected portfolio requirements based on job description analysis. Indicates whether the client requires, prefers, or doesn't need portfolio samples from applicants. Examples: Required, Not Required, Optional

• Explicit Mention Of Agency (ai_explicit_mention_of_agency) - select: AI-detected explicit mention of agency preferences in the job posting. Indicates whether the client welcomes agencies, prefers individual freelancers, or has no specific preference. Examples: No Mention, No Agencies, Agencies Welcome

• Complexity Score (ai_complexity_score) - select: AI-detected complexity score of the job based on the project requirements and deliverables. Examples: High, Low, Moderate

• Budget Estimation Indicators (ai_budget_estimation_indicators) - select: AI-detected budget estimation indicators based on job description analysis. Categorizes jobs by their apparent budget level: High Budget for premium projects, Moderate Budget for standard projects, Low Budget for cost-conscious projects, or Not Specified when budget indicators are unclear. Examples: High Budget, Moderate Budget, Low Budget

• Client's Technical Understanding (ai_clients_technical_understanding) - select: AI-detected assessment of the client's technical understanding based on how they describe their project requirements. Helps identify whether the client has deep technical knowledge, moderate understanding, basic knowledge, or expert-level expertise in the domain. Examples: Moderate, High, Low

• Summary (ai_summary) - text: AI-generated summary of the job description. Provides a concise overview of the job requirements and responsibilities. Examples: This job is a full-stack developer role for a startup. The ideal candidate will have experience with React, Node.js, and PostgreSQL., This job is a data analyst role for a consulting firm. The ideal candidate will have experience with SQL, Python, and data visualization tools.

System Metadata

• Created At (created_at) - date: Timestamp when this job record was created in our system (not the Upwork posting date). Examples: 2024-01-20T14:30:00Z

🤖 AI-Enriched Sample Data

Here are 5 real examples from our dataset showcasing the AI insights you'll get:

📝 Sample 0 - HR Officer (Talent Acquisition) | Remote

AI Summary: The client seeks a remote HR Officer specializing in AI-driven talent acquisition and HR operations to manage recruiting pipelines, onboarding, HRIS upkeep, and performance tracking with a final deliverable of streamlined, AI-optimized HR processes achieving specific KPIs. They expect 2–4+ years of relevant experience, strong AI and HRIS tool proficiency, flexibility across time zones, and adherence to a $1000/month budget with incentives based on performance. Watch for scope creep around demanding 5–7 days availability during busy periods and the need to consistently hit aggressive KPIs under rapid scaling; this role offers a standout chance to lead AI-enabled HR transformation in a mission-driven company.

🚨 Urgency: Moderately Urgent ⏱️ Duration: Long-Term

📋 Pre-Apply Requirements: Submit resume/CV with HR + TA experience and tools used, Provide a short cover letter (≤1 page) explaining value addition

🤖 Anti-Bot Phrase: What's your HealthType?

🏷️ Named Entities: Shae Group, Workable, Breezy, Lever, Skillspot Ai, Google Workspace, healthtypetest.org

🏢 Agency Mention: No Mention

📝 Sample 1 - Senior AI/ML Engineer with experience DL, NLP, LLMs & CV

AI Summary: You’ll architect, lead, and deploy a full-scale AI platform leveraging cutting-edge LLMs and AI infrastructure to deliver real-time partnership intelligence with strong cross-team collaboration; the end product is a production-ready, scalable AI system integrated with data and backend pipelines. The client demands a senior engineer with 7+ years experience, deep expertise in LLM fine-tuning, production AI systems, AWS deployment, and AI safety, working full-time without multitasking on other projects. Watch for the strict no-multitasking policy and heavy emphasis on technical leadership and collaboration, which signals a high-expectation startup environment requiring proactive communication and ownership.

🚨 Urgency: Not Urgent ⏱️ Duration: Long-Term

📋 Pre-Apply Requirements: Answer AI screener questions to demonstrate ability to fulfill position requirements, Do not apply if working on multiple projects simultaneously

🤖 Anti-Bot Phrase: If taking the time to answer these questions is too much and if you really don't know how to do the required tasks, please do not submit a proposal.

🏷️ Named Entities: GPT-4, Claude, Llama, LoRA, QLoRA, PyTorch, TensorFlow, Hugging Face, LangChain, LlamaIndex, Pinecone, Weaviate, Chroma, AWS SageMaker, AWS Bedrock, AWS Lambda, AWS ECS, Next.js, NestJS, PostHog, Mixpanel, Grafana

🏢 Agency Mention: No Agencies

📝 Sample 2 - Full Website Redesign & Development for a Medical Device Reprocessing Provider (with Geo-Redirect)

AI Summary: Build a completely new, responsive website from scratch for a medical device reprocessing firm, including original content, infographics, geo-routing by region, an AI chatbot with text and voice, and CRM integration, all optimized for SEO and performance. The client expects a healthcare-experienced team delivering within 8-10 weeks, with clear proposals starting “Crispy croissants are the best,” detailed quotes covering design through support, and adherence to HIPAA and similar regulations. Watch for scope creep from extensive chatbot and CRM features, compliance demands, and a strict callout phrase signaling attentiveness—a strong opportunity for agencies skilled in complex, compliant healthcare platforms.

🚨 Urgency: Moderately Urgent ⏱️ Duration: Mid-Term

📋 Pre-Apply Requirements: Start proposal with the phrase: "Crispy croissants are the best."

🤖 Anti-Bot Phrase: Crispy croissants are the best

🏷️ Named Entities: Zoho, Salesforce, WCAG 2.1, HIPAA, GDPR, U.S., Canada

🏢 Agency Mention: Agencies Welcome

📝 Sample 3 - Vision AI Data Scientist

AI Summary: Aloha Thalmaar, you need a data scientist to develop and deploy Large Language Model solutions integrated with hardware sensors and camera systems, delivering a functional pilot within three months. The ideal candidate must have 3+ years in LLMs, hands-on hardware integration experience, expertise in Python and AI frameworks, and be comfortable with the trial period before full-time hiring. Watch for potential scope creep as the role spans AI research, hardware collaboration, API development, and cloud deployment, but this also offers a unique chance to work on cutting-edge multimodal AI systems combining vision and language.

🚨 Urgency: Moderately Urgent ⏱️ Duration: Short-Term

📋 Pre-Apply Requirements: Write Aloha Thalmaar at the top

🤖 Anti-Bot Phrase: Write Aloha Thalmaar at the top

🏷️ Named Entities: Thalmaar, GPT, BERT, Llama, PyTorch, TensorFlow, Hugging Face, AWS, Azure, GCP

🏢 Agency Mention: No Mention

📝 Sample 4 - E-commerce Manager for TikTok Shop & Shopify Growth

AI Summary: The client needs an experienced e-commerce manager to fully set up and launch two new stores on TikTok Shop and Shopify, delivering initial sales and scalable growth with product sourcing, marketing, automation, and team management. They expect proven track records with measurable results, a detailed phased plan for the first two months, budget forecasts starting around $2K–$5K, and expertise in AI tools, TikTok algorithm, and influencer marketing for rapid scaling. Watch for scope creep in the broad responsibilities spanning marketplaces, content, ads, and outsourcing, but there’s a strong opportunity for long-term collaboration and revenue sharing.

🚨 Urgency: Moderately Urgent ⏱️ Duration: Long-Term

📋 Pre-Apply Requirements: Provide real case studies with numbers (GMV growth, profit, successful launches), Submit a step-by-step plan for the first 1–2 months including weekly and monthly milestones, Include approximate ad and inventory budget (starting with $2K–$5K), Provide financial projections: projected GMV (pessimistic / realistic / optimistic), gross revenue, net profit, and break-even timeline, Propose automation tools and partner platforms to accelerate sales, Offer service pricing considering the store is new

🤖 Anti-Bot Phrase: 🚨🚨🚨🚨🚨 IMPORTANT — PLEASE READ BEFORE APPLYING 🚨🚨🚨🚨🚨

🏷️ Named Entities: TikTok Shop, Shopify, Pipiads, Minea, Dropship IO, Amazon Movers & Shakers, CJ Dropshipping, Zendrop, AutoDS, TikTok, Instagram Reels, YouTube Shorts, Facebook Reels, Spark Ads, TikTok Ads, Meta Ads

🏢 Agency Mention: No Mention

💡 This is just a tiny sample! Your download includes 500000+ AI-enriched jobs with 11 different AI insight fields.

📈 Use Cases

• 📊 Data Analysis: Analyze job market trends and pricing patterns
• 🔬 Research Projects: Academic or business research on freelance markets
• 🤖 ML Training: Train machine learning models on job data
• 📈 Market Intelligence: Understand demand for different skills
• 🎯 Business Strategy: Inform pricing and positioning decisions
• 📱 App Development: Build job matching or recommendation systems

🆘 Support & Resources

• 📚 Field Reference: Complete field documentation included above
• 📧 Contact: support@hyperbach.com
• 🔄 Updates: Database updated weekly with fresh job data
• 💾 Download Issues: Contact us if you have any problems with file downloads

🎯 Ready to analyze Upwork job market data? Use the code examples above to get started with your analysis!

Last updated: 2025-09-13 18:55:16 UTC