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Handshake AI Fellowship Overview & FAQs (for EDU Partners)

Jaci
  • Updated

The Handshake AI Fellowship is an initiative from Handshake that offers highly skilled students, graduates, and researchers paid, part-time opportunities to contribute to the training and evaluation of large language models (LLMs).

While Handshake AI is a distinct initiative within Handshake, it is fully supported by our platform, infrastructure, and commitment to student protections. 

 

Handshake AI Overview

The Handshake AI Fellowship connects selected candidates, known as Fellows, with AI labs to validate and improve model outputs. Fellows contribute by designing and evaluating AI prompts and responses in their academic fields. 

Goals: 

  • Enable Fellows to showcase domain expertise in collaboration with leading AI labs
  • Support skill development in advanced AI prompting and evaluation
  • Offer competitive compensation for contributing to innovative AI research

Responsibilities:

  • Creating prompts in the Fellow’s field of expertise
  • Evaluating or comparing AI-generated responses
  • Correcting and improving content with academic citations

Employment type:

  • Part-time, remote, and asynchronous
  • Fellows set their own schedules (typically 5 - 20 hrs/week)
  • Projects vary in length from 2 weeks to 3+ months
  • All Fellows are hired as 1099 independent contractors

This setup supports participation by international graduate students, where visa conditions permit. More details available in Fellowship Work Authorization Eligibility.

Compensation:

  • Hourly rates are $30–$125, based on education level, expertise, and project
  • All compensation is transparent before project acceptance
  • Fellows are contracted and paid directly by Handshake, not the partnering AI lab

 

Application & Selection Process

Jobs are listed both on:

We encourage you to promote these roles to students at your institution!

Applications are reviewed on a rolling basis according to partner lab needs, and candidates are selected based on their academic background and domain knowledge.

  • Most roles require graduate-level expertise (Master’s, PhD, or Postdoc).
  • In some cases, individuals without a formal degree but with demonstrated subject-matter expertise may be considered. 

Selection timelines vary–just because a candidate has not heard back does not mean they were not selected! When there's a project that matches their expertise, our team will reach out with an invitation via email. 

More details are available in the following resources: 

 

Program Structure & Expectations

Selected Fellows are offered tasks based on their availability and subject matter expertise. 

Commitment expectations are made clear at the beginning of each project, and participation in individual projects can be accepted or declined depending on scheduling needs.

Each project determines its own onboarding and training requirements, as outlined by the Project Lead. These details and instructions are communicated once fellows are accepted, and Fellows are compensated for project onboarding time. 

Every Fellow who is accepted goes through our general onboarding flow, which has ~2 hours of learning modules on Canvas. They then complete a knowledge quiz, and are passed along to a live practice task where they get feedback from reviewers. They are compensated for this time.

Handshake plans to continue to add more courses to help candidates upskill as they think about their careers in this new AI workforce.

 

Additional FAQs

Will Fellows be exposed to sensitive or explicit content? 

  • No. Handshake does not engage in projects involving vulgar, violent, or sexually explicit material. Students are only hired to contribute based on their subject-matter knowledge.

 

Are there ethical considerations? 

  • Fellows play a key role in:
    • Identifying inaccuracies and bias in model outputs
    • Validating information with trusted, academic sources
    • Supporting the development of accurate, inclusive, and responsible AI

We believe ethical AI starts with ethical training and diverse academic voices.
 

What safeguards are in place?

  • Every project is internally reviewed before launch
  • Tasks are regularly monitored for clarity, fairness, and accuracy
  • Contributors come from a wide range of institutions and backgrounds, helping to reduce bias in training and feedback

 

Are fellows allowed to use external AI tools like ChatGPT or Claude?

  • No. The use of external AI tools for prompt ideation, solution writing, or editing is strictly prohibited. All work must be original. An internal LLM and Grammarly integration are provided when needed. Fellows are provided clear guidelines about LLM usage and IP during onboarding. 

 

What are the IP considerations for Handshake AI? 

  • There is no transfer of any previous or future IP from the fellows to Handshake or any of our partnering labs. Any materials created within the Program, on official Program channels, are owned by Handshake and their partnering labs.
  • If fellows cite original works in their AI prompting, they grant royalty-free license to both Handshake and our partners to use their works for upcoming model training. Fellows do not transfer any IP in that situation. 

 

Who are the AI labs you're partnering with?

  • While we can’t share names due to confidentiality agreements, we are working with leading labs focused on building general-purpose LLMs.
     

How long has Handshake been doing this?

  • HandshakeAI is a new initiative launched in response to rising demand for academic expertise in AI training. While still small compared to our core business, we believe this is a meaningful way to offer students valuable real-world experience.

 

Is this a long-term focus for Handshake?

  • We’re still in the early stages. While our long-term direction will evolve, we’re still relying on feedback from Fellows and schools.