Research Engineer: Agentic AI & RL for Chip Design

Normal Computing Corp.; New York, Northern (NY, KY); Hybrid; USD 150,000 - 220,000; Full time

Job summary

Normal Computing is an applied AI company building foundational hardware and software for the semiconductor industry. We hire a Research Engineer to push the frontier of agentic LLMs and reinforcement learning for Normal EDA, our platform for semiconductor design automation.

You will design experiments, build agents, curate datasets, and write production-quality research code in collaboration with engineers.

Qualifications

• PhD in CS/AI/ML with publications ideally in multi-agent RL, agentic AI, or RL for language/code.
• Demonstrated ability to turn research into working systems.
• Experience designing evaluation environments and reward models for sequential/agentic tasks.

Responsibilities

• Build multi-agent systems for code generation that interact with EDA tools, propose fixes, and iterate through chip design and verification flows.
• Build research prototypes that integrate with production agentic code generation tool and productionize wins.
• Create RL environments and evaluations for agents, explore proxy rewards and consider speed/accuracy tradeoffs of custom tools.
• Generate datasets from silicon collateral sources such as RTL, testbenches, VIPs, and chip specifications; maintain data cards and licensing.
• Analyze experiments with ablations; document results and drive progress with technical rigour.
• Stay current on LLM agents, RL (offline/online, RLHF/RLAIF), constrained decoding, and program synthesis.

Skills

Clear communicator

Ability to turn research into working

Education

PhD in CS/AI/ML

Tools

Python

PyTorch

JAX

HuggingFace

Job description

Normal Computing is an applied AI company building foundational hardware and software for the semiconductor industry. We hire a Research Engineer to push the frontier of agentic LLMs and reinforcement learning for Normal EDA, our platform for semiconductor design automation.

You will design experiments, build agents, curate datasets, and write production-quality research code in collaboration with engineers.