AI Research Engineer

YOUR ROLE IN OUR MISSION We’re hiring an AI Research Engineer to push the frontier of agentic LLMs and reinforcement learning for our agentic code generation tool. You’ll design and run experiments, build agents, curate datasets from complex technical documents (e.g., chip specifications), and create rigorous evaluations. You’ll write production‑quality research code and work closely with engineering to ship improvements to customers. Leadership not required—impact through research and building is. RESPONSIBILITIES - Design and implement multi‑agent and RL approaches for agentic code generation and tool‑use. - Build research prototypes that integrate with our agentic code generation tool; collaborate to productionize wins. - Create evaluation suites: task specs, pass/fail checkers, coverage, cost/latency dashboards. - Acquire and curate datasets from PDFs/logs/tables; generate synthetic data where appropriate; maintain data cards and licensing. - Analyze experiments with disciplined ablations; document results and decisions. - Stay current on LLM agents, RL (offline/online, RLHF/RLAIF), constrained decoding, and program synthesis. WHAT MAKES YOU A GREAT FIT - PhD in CS/AI/ML (or equivalent research experience) with publications ideally in multi‑agent RL, agentic AI, or RL for language/code. - Strong Python and ML framework experience (PyTorch preferred; JAX/HF a plus). - Demonstrated ability to turn research into working systems; reproducibility mindset (tests, seeds, configs, logging). - Experience designing eval harnesses and success metrics for sequential/agentic tasks. - Comfortable with data acquisition/curation from documents/logs; good instincts about data quality and licenses. - Clear communicator who partners well with engineers. BONUS POINTS FOR - Research on program synthesis/codegen, constrained decoding, or execution‑based rewards. - Experience with offline RL from tool traces or human corrections. - Open‑source contributions (e.g., CleanRL, RLlib, Auto