Research Intern, Agent RL Training

What you'd do

• Collaborate with your full-time mentor to identify high-impact research directions for applying LLMs to NewsBreak’s products
• Independently run end-to-end SFT experiments on LLM-based agents, and assist with RL-related exploration such as reward design and training iteration
• Curate and build high-quality training datasets: instruction-following, preference pairs, agent trajectories, and synthetic data
• Contribute to public publications; we encourage and support top-venue submissions during your internship

What they want

• Highly motivated and committed: willing to put in extra hours when needed to push projects across the finish line
• Genuine passion for research: you read papers for fun, tinker with models on weekends, and care deeply about advancing the field
• Independently capable of end-to-end model SFT: with basic understanding of RL-based post-training methods (RLHF, DPO, PPO, GRPO, etc.)
• Excellent taste in model behavior: able to reason about what “good” looks like across user-facing domains and articulate why
• Strong Python and PyTorch skills