Engineering Expert - Remote AI Fellowship
Listing checked September 18, 2026 · pay as published by Handshake AI
Overview
Handshake AI brings together PhD and master's level engineers, with a focus on hardware engineering, to sharpen how large language models handle specialized technical subjects. The AI Fellowship runs all year, and project openings shift by domain and availability. Fellows work on a remote, asynchronous schedule for about 10 to 20 hours each week. Typical project tasks include writing domain-specific prompts and judging LLM responses, while also researching topics that matter to your field with AI tools at your side. The program accepts U.S.-based doctoral students, postdocs, and recent graduates who hold valid work or training authorization.
What You'll Do8
- 1Build prompts that test how well an LLM explains core concepts in hardware engineering and its subfields.
- 2Review model answers for accuracy, reasoning, and domain fit, then record where the model misses key details.
- 3Research engineering topics tied to your expertise, using AI tools to collect references and context.
- 4Label or rank model outputs to create training signals for partner AI labs.
- 5Work through assigned projects on an asynchronous schedule and meet the agreed 10 to 20 hours per week.
- 6Follow project rules for data quality, privacy, and confidentiality.
- 7Coordinate with AI lab partners through written updates and shared project spaces.
- 8Track advances in your engineering subdomain to shape new prompt ideas.
Requirements7
- 1Master's, doctoral, or postdoctoral standing in engineering or a related field. Current enrollment in a master's or PhD program counts.
- 2U.S.-based location and valid work or training authorization, such as F-1/OPT, J-1, or H-1B.
- 3Candidates on STEM OPT who need an i-983 cannot join. Approved i-983, pre-grad OPT, CPT, J-1, and H-1B situations are unaffected.
- 4Comfort with independent, asynchronous project work alongside AI labs.
- 5Expertise that can outmatch current AI systems in explaining important concepts in your engineering field.
- 6Availability of about 10 to 20 hours per week.
- 7Strong writing skills for prompt creation and response review.
Who Should Apply
An ideal candidate holds a master's, PhD, or postdoc in hardware engineering or a related engineering area, lives in the U.S., and has work authorization that does not require an i-983. The role suits engineers who can give 10 to 20 hours each week to asynchronous projects and who want to test their expertise against modern LLMs. The role is less suitable for anyone seeking a permanent full-time position with a fixed project pipeline or for engineers outside the U.S. who lack work or training authorization. A common reason applications score low is a vague description of domain knowledge. Another is an unresolved i-983 requirement, since Handshake cannot accommodate that case at this time.
Salary Insight
The listing advertises up to $75.00 per hour. For PhD-level AI training work, that rate sits above many general annotation roles and matches the premium that specialized engineering expertise commands. Final pay may depend on the project, domain, and your placement.
Pay and demand for Machine Learning & AI roles
AggregatedTypical pay
$75/hour
This role
up to $75/hr
Most Machine Learning & AI roles pay $55–$100 per hour. This role's pay falls inside that range.
Based on 564 similar roles that publish pay · 91 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.
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- Listed in last 30 days
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Hiring most right now: micro1 (280) · Mercor (90) · Handshake AI (62)
Most requested skills · share of roles
- python18%
- technical writing9%
- llm evaluation8%
- ai evaluation7%
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Compensation
Up to $75/hr
Required Skills
Application Tip
Name one hardware engineering subdomain, such as chip design, robotics, or embedded systems, and describe a concept you can explain better than a current LLM. Then state your U.S. work authorization status and whether you need an i-983, because that detail decides eligibility for this fellowship.
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