About Handshake AI
Handshake is building the career network for the AI economy. Our three-sided marketplace connects 18 million students and alumni, 1,500+ academic institutions across the U.S. and Europe, and 1 million employers to power how the next generation explores careers, builds skills, and gets hired.
Handshake AI is a human data labeling business that leverages the scale of the largest early career network. We work directly with the world’s leading AI research labs to build a new generation of human data products. From PhDs in physics to undergrads fluent in LLMs, Handshake AI is the trusted partner for domain-specific data and evaluation at scale.
This is a unique opportunity to join a fast-growing team shaping the future of AI through better data, better tools, and better systems—for experts, by experts.
Now’s a great time to join Handshake. Here’s why:
Leading the AI Career Revolution: Be part of the team redefining work in the AI economy for millions worldwide.
Proven Market Demand: Deep employer partnerships across Fortune 500s and the world’s leading AI research labs.
World-Class Team: Leadership from Scale AI, Meta, xAI, Notion, Coinbase, and Palantir, just to name a few.
Capitalized & Scaling: $3.5B valuation from top investors including Kleiner Perkins, True Ventures, Notable Capital, and more.
About the Role
As an AI Tutor, Materials Science Specialist, you will be instrumental in improving AI’s understanding of Materials Science by reviewing expert-annotated data using proprietary software. Your subject expertise will help refine AI-generated content, ensuring accuracy in concepts, material properties, and applications. This role requires analytical thinking, adaptability, and a strong passion for AI in scientific education.
This is a remote contract position with variable time commitments. The services provided are supplementary and distinct from Handshake’s core business operations.
Day-to-day responsibilities include
Using proprietary software to analyze AI-generated Materials Science content and provide expert feedback
Ensuring high-quality data curation to enhance AI model accuracy
Collaborating with technical teams to refine annotation tools and methodologies for Materials Science-related tasks
Evaluating AI-generated and human responses across disciplines including biomaterials, nanomaterials, electronic materials, and structural materials
Interpreting, analyzing, and reviewing tasks based on evolving guidelines
Desired Capabilities
PhD in Materials Science or a closely related field (in progress or completed within the last 10 years)
Proficiency in materials characterization techniques, property analysis, and laboratory methodologies
Excellent communication and organizational abilities
Ability to make independent evaluations based on limited data
Passion for AI, scientific education, and technology
Extra Credit
Research experience with published work in a reputable Materials Science journal
Experience in AI-assisted education or tutoring
Teaching experience (professor, lecturer, or tutor in Materials Science or related engineering fields)
Experience in technical writing, science communication, or professional scientific writing
Additional Information
Engagement: Contract, remote, variable time commitment
Schedule: Flexibility required, with some evening and weekend availability
Location: Fully remote (no visa sponsorship available)
Technical Requirements: Personal device supporting Windows 10 or macOS Big Sur 11.0+ and reliable access to a smartphone