AI Research Engineer

Department: Engineering

Location: New York City, London, Zurich, Silicon Valley, Copenhagen

Compensation: $200K – $400K • Offers Equity

Employment Type: FullTime

Normal Computing | Build with Us

Normal is an applied AI company solving the hardest problems in AI and silicon. We build foundational hardware and software for the semiconductor industry, critical AI infrastructure, and the broader systems that power our world, in partnership with the worlds most advanced institutions. We work as one team across New York City, Silicon Valley (Mountain View), London, Copenhagen, and Seoul.

The Role

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.

What You Will Own

• 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

• 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.

Equal Employment Opportunity Statement

Normal Computing is an Equal Opportunity Employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, veteran status, or any other legally protected status.

Accessibility Accommodations

Normal Computing is committed to providing reasonable accommodations to individuals with disabilities. If you need assistance or an accommodation due to a disability, please let us know at accommodations@normalcomputing.com.

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