Student Researcher

🇺🇸In-Person - San Francisco, CA$22–$28/hri1h ago

Higher Ed Research AI Research Machine Learning Llm Post Training Nlp Research Evaluation Methodology

Summary

Student Researcher role at Handshake AI focused on building data engines for large language models, with projects spanning LLM post-training, evaluation, and data efficiency. Selected research contributions will ship into production and target publication at top-tier venues.

Key Responsibilities: Own a scoped research project mentored by a senior scientist, conducting hands-on experiments in areas such as RLHF pipelines, LLM evaluation benchmarks, or data efficiency methods. Deliver archive-ready manuscripts or top-tier conference submissions as the explicit project goal.

Skills & Tools: Proficiency in PyTorch, JAX, and distributed training frameworks; strong empirical rigor and ability to tackle open-ended AI research questions. Prior experience with RLHF, evaluation tooling, data selection, or open-source LLM contributions is highly valued.

Qualifications: Current PhD student in Computer Science, Machine Learning, NLP, or related field with a publication track record at top venues (NeurIPS, ICML, ACL, EMNLP, ICLR). Demonstrated hands-on experience training and experimenting with large language models.

Location: San Francisco, California (full-time in-person or part-time remote options available); September – December 2026.

Compensation: $22–$28/hr (estimated)

Job Description

About Handshake

Handshake is the career network for the AI economy. 20 million knowledge workers, 1,600 educational institutions, 1 million employers (including 100% of the Fortune 50), and every foundational AI lab trust Handshake to power career discovery, hiring, and upskilling, from freelance AI training gigs to first internships to full-time careers and beyond. This unique value is leading to unparalleled growth; in 2025, we tripled our ARR at scale.

Why join Handshake now:

Shape how every career evolves in the AI economy, at global scale, with impact your friends, family and peers can see and feel
Work hand-in-hand with world-class AI labs, Fortune 500 partners and the world’s top educational institutions
Join a team with leadership from Scale AI, Meta, xAI, Notion, Coinbase, and Palantir, among others
Build a massive, fast-growing business with billions in revenue

About the Role

Handshake AI builds the data engines that power the next generation of large language models. Our research team works at the intersection of cutting-edge model post-training, rigorous evaluation, and data efficiency. Join us for a Student Researcher engagement this fall where your work can ship directly into our production stack and become a publishable research contribution. The role can take place full time in person in San Francisco or potentially part time remote.) The target window of time is September - December 2026.

Projects You Could Tackle

LLM Post-Training: Novel RLHF / GRPO pipelines, instruction-following refinements, reasoning-trace supervision.
LLM Evaluation: New multilingual, long-horizon, or domain-specific benchmarks; automatic vs. human preference studies; robustness diagnostics.
Data Efficiency: Active-learning loops, data value estimation, synthetic data generation, and low-resource fine-tuning strategies.

Each intern owns a scoped research project, mentored by a senior scientist, with the explicit goal of an archive-ready manuscript or top-tier conference submission.

Desired Capabilities

Current PhD student in CS, ML, NLP, or related field.
Publication track record at top venues (NeurIPS, ICML, ACL, EMNLP, ICLR, etc.).
Hands-on experience training and experimenting with LLMs (e.g., PyTorch, JAX, DeepSpeed, distributed training stacks).
Strong empirical rigor and a passion for open-ended AI questions.

Extra Credit