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.
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.
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.
Privacy Notice
By submitting your application, you agree that Normal Computing may collect, use, and store your personal information for employment-related purposes in accordance with our Privacy Policy.
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.
