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AI Research Engineer

  • Source: Ashby
  • Normal Computing
  • $200,000 to $400,000 /yr
  • On-site
  • New York City
  • Full-Time
  • Mid level

Job Description

  • 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- Strong Python and ML framework experience (PyTorch preferred; JAX/HF a plus)
  • PhD in CS/AI/ML (or equivalent research experience) with publications ideally in multi‑agent RL, agentic AI, or RL for language/code
  • Demonstrated ability to turn research into working systems; reproducibility mindset (tests, seeds, configs, logging)
  • Clear communicator who partners well with engineers
  • 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
  • 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

Skills

  • Python
  • PyTorch
  • LangGraph
  • crewai
  • Transformers
  • ashby

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