AI Research Engineer
Normal Computing CorporationBase Salary
$200k - $400k/yr
Responsibilities
- Design and implement multi-agent and reinforcement learning approaches for agentic code generation and tool use.
- Build research prototypes that integrate with the agentic code generation tool and collaborate with engineering to productionize successful approaches.
- Create evaluation suites with task specifications, pass/fail checkers, coverage measures, and cost or latency dashboards.
- Acquire and curate datasets from PDFs, logs, and tables; generate synthetic data when appropriate; and maintain data cards and licensing information.
- Analyze experiments using disciplined ablations and document results and decisions.
- Stay current on LLM agents, offline and online reinforcement learning, RLHF, RLAIF, constrained decoding, and program synthesis.
Requirements
- PhD in CS, AI, or ML, or equivalent research experience, ideally with publications in multi-agent reinforcement learning, agentic AI, or RL for language/code.
- Strong Python and machine learning framework experience, with PyTorch preferred and JAX or Hugging Face a plus.
- Ability to turn research into working systems with reproducible tests, seeds, configurations, and logging.
- Experience designing evaluation harnesses and success metrics for sequential or agentic tasks.
- Experience acquiring and curating data from documents and logs, with attention to data quality and licensing.
- Clear communication and effective partnership with engineers.
- Bonus qualifications include research in program synthesis, code generation, constrained decoding, execution-based rewards, or offline RL from tool traces or human corrections.
- Open-source contributions to projects such as CleanRL, RLlib, AutoGen, LangGraph, CrewAI, or Transformers are a plus.
- Familiarity with semiconductor or chip domains and a track record of shipping research to production are advantageous.
About Normal Computing Corporation
At Normal, we're rewriting AI foundations to advance the frontier of reasoning and reliability in the physical world. We are tackling problems across semiconductors and industrials with a mix of interdisciplinary approaches across the full stack: from probabilistic software infrastructure and algorithms to hardware and physics, enabling AI that can reason and understand its own limits. We understand that our technology is only as powerful as the people behind it. Every employee drives significant impact within our products, often working directly with customers and embedding across our tightly-knit team. Our team members are driven by curiosity and passion for solving some of the most challenging problems in the world of atoms. Normal was founded in 2022 by engineers and scientists that pioneered industry-leading Physics + ML tools for next-gen AI at Google Brain and Google X.