AI Research Intern, Handshake

• 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

Desirable

• To start between December 1st and January 15th
• Our AI team is rapidly building a new generation of human data products—from expert annotation platforms to AI interviewers and seamless payout infrastructure—all designed to accelerate research and improve model performance
• We’ve assembled a world-class team from YC, Notion, Scale, Coinbase, Palantir, and more, and we’re working directly with many of the world’s leading AI research labs. 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
• 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 focused winter 2025 internship where your work can ship directly into our production stack and become a publishable research contribution
• 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 by spring 2026