AI Research Engineer

Who you are

• 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
• 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, AutoGen, LangGraph, CrewAI, Transformers)
• Familiarity with semiconductor/chip domains or other complex technical specs
• Track record of shipping research to production and measuring impact

What the job involves

• 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
• 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