Technical AI Evaluation Contributor (Remote US)
Listing checked September 26, 2026 · pay as published by Handshake AI
Overview
Handshake AI hires experienced software engineers, data scientists, and quants for part-time contract work that supports AI research. You will create expert-level technical problems and judge AI-generated answers for accuracy, feasibility, and alignment with real system design, modeling, or trading work. The project runs on an ongoing basis, so you can add it alongside a current role. No set schedule or minimum hour requirement applies.
What You'll Do5
- 1Build expert-level technical problems and scenarios that reflect real system design, modeling, or quantitative analysis.
- 2Evaluate AI-generated responses for technical accuracy, practical feasibility, and how well they match real workflows.
- 3Write structured feedback that helps AI models improve reasoning.
- 4Draw on hands-on experience from production systems, models, or quantitative strategies to ground each task.
- 5Set your own pace with no schedule or minimum hours.
Requirements8
- 1At least 1 year of professional experience at a top company as a software engineer, data scientist, or quant.
- 2Bachelor's degree in Computer Science, Data Science, Statistics, Mathematics, or another quantitative field.
- 3Demonstrated depth in one area: software engineering (system design, backend or infrastructure, production code), data science (machine learning, statistical modeling, applied ML), or quantitative finance (quant research, trading strategies, risk modeling).
- 4Based in the United States.
- 5Strong written communication and close attention to detail.
- 6Ability to explain complex technical concepts in clear terms.
- 7Ability to work on your own in a remote, asynchronous environment.
- 8Bonus: experience at a recognized top-tier tech company or quant firm.
Who Should Apply
The right candidate has at least a year of hands-on work at a top company as a software engineer, data scientist, or quant, plus a quantitative degree and deep knowledge in one sub-domain. You enjoy breaking down system design, modeling, or trading problems and explaining where AI answers fall short. The role fits people who already hold a technical job and want flexible, project-based side work. The role is less suitable for early-career candidates without professional technical experience, for anyone outside the United States, or for generalists with no depth in software engineering, data science, or quantitative finance. Applications often score low when candidates cannot show the required 1 year at a top company, hold a degree outside a quantitative field, or give vague feedback with no concrete technical reasoning.
Salary Insight
The listing sets pay at $105.00 per hour. That rate sits above many part-time AI evaluation contracts, and it matches the senior technical depth the client seeks. Because the work is project-based, your total earnings depend on how many hours you choose to take on.
Pay and demand for Machine Learning & AI roles
AggregatedTypical pay
$75/hour
This role
$105/hr
Most Machine Learning & AI roles pay $50–$100 per hour. This role's pay sits above that range.
Based on 551 similar roles that publish pay · 168 publish only a top rate; those count at the rate they gave
Rates shown per hour. Yearly and monthly pay converted; one-time fees and non-USD pay are not included.
- Live similar roles
- 628
- Listed in last 30 days
- 426
- Remote
- 98%
Hiring most right now: micro1 (220) · SME Careers (141) · Mercor (76)
Most requested skills · share of roles
- ai training18%
- python18%
- llm evaluation18%
- trainer feedback13%
Figures from Machine Learning & AI roles live on NearSkill when this page loaded. A role can close before you apply, so check the listing itself.
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Compensation
$105/hr
Required Skills
Application Tip
Name the sub-domain you know best and attach one concrete proof point: a production system you shipped, a model you built, or a trading strategy you designed. Add scale or results, such as user counts, latency gains, or Sharpe ratio. That evidence maps to the three screens: top-company experience, quantitative degree, and sub-domain depth.
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