About the role#
We are looking for a Research Intern to join the Agent RL Training team. You will be paired with a full-time mentor to explore how to apply large language models to core business areas, including content understanding, recommendation, agentic web browsing, and autonomous multi-step task completion. This is a hands-on research role where you will independently drive experiments, propose novel ideas, and iterate quickly.
What you'll do#
- Collaborate with your mentor to identify high-impact research directions for applying LLMs to products.
- Independently run end-to-end SFT experiments on LLM-based agents and assist with RL-related exploration, including reward design and training iteration.
- Curate and build high-quality training datasets, including instruction-following, preference pairs, agent trajectories, and synthetic data.
- Contribute to public publications, with support for top-venue submissions during your internship.
What you'll need#
- Strong Python and PyTorch skills.
- Independent capability in end-to-end model SFT with a basic understanding of RL-based post-training methods such as RLHF, DPO, PPO, or GRPO.
- Excellent taste in model behavior, with the ability to reason about and articulate what constitutes high quality across user-facing domains.
- Genuine passion for research, demonstrated by reading papers, tinkering with models, and a commitment to advancing the field.
- High motivation and commitment, including the willingness to put in extra hours when necessary to complete projects.
- Pursuing or holding a degree in Computer Science, Data Science, or Mathematics.
Location & details#
- Location: On-site in Mountain View, California.
- Type: Full-time, paid internship.
- Term: Rolling.
