AI Research Engineer

About the Company

Normal Computing builds silicon that turns thermal noise from an obstacle into a computational resource. We co-design the full stack: AI-native EDA systems and advanced ASICs. Backed by $85M+ from leading deep-tech investors, we work across New York, Silicon Valley, London, Copenhagen, and Seoul.

Responsibilities

• Design and implement multi-agent and RL approaches for agentic code generation and tool use
• Build research prototypes that integrate with the platform and collaborate to productionize wins
• Create evaluation suites including task specs, pass/fail checkers, and cost/latency dashboards
• Acquire and curate datasets from PDFs, logs, and tables, including synthetic data generation
• Analyze experiments with disciplined ablations and document results
• Stay current on LLM agents, RL, constrained decoding, and program synthesis

Requirements

• PhD in CS/AI/ML or equivalent research experience
• Strong Python and ML framework experience (PyTorch preferred)
• Ability to turn research into working systems with a reproducibility mindset
• Experience designing eval harnesses and success metrics for agentic tasks
• Proficiency in data acquisition and curation from documents and logs

Preferred Qualifications

• Research on program synthesis, codegen, or constrained decoding
• Experience with offline RL from tool traces or human corrections
• Open-source contributions to libraries like CleanRL, RLlib, AutoGen, or Transformers
• Familiarity with semiconductor or chip domains