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Research Engineer, Agentic EDA
Summary by AIEngineer.careers
Research Engineer, Agentic EDA is a AI Research Engineer role (full-time). with Normal Computing Corporation. in NEW YORK, US. Compensation shown: $200K–$400K. Imported listing (source: drjobpro.com). Apply on the employer's site (drjobpro.com).
Imported listing (source: drjobpro.com) · Apply on drjobpro.com
NEW YORK · US
$200K–$400K
Full-time
SENIOR
The sections below reproduce the third-party job description for reference. AIEngineer.careers does not write or control this text.
Imported job description
Sourced from drjobpro.com
Normal Computing is seeking a Research Engineer to advance agentic LLMs and reinforcement learning for semiconductor design automation. The role involves building multi-agent systems that interact with EDA tools, creating RL environments, and curating high-quality datasets from silicon collateral. You will bridge the gap between academic research and production-grade AI infrastructure.
Responsibilities
- Build multi-agent systems for code generation interacting with EDA tools (simulations, formal verification, physical design).
- Create RL environments and evaluations for agents, exploring proxy rewards and speed/accuracy tradeoffs.
- Generate and curate datasets from RTL designs, VIPs, and chip specifications; maintain data cards and licensing.
- Analyze experiments with disciplined ablations and document results to drive technical progress.
- Collaborate with engineering to productionize research prototypes and ship improvements.
Requirements
- PhD in CS/AI/ML or equivalent research experience with publications in multi-agent RL, agentic AI, or RL for language/code.
- Strong proficiency in Python and ML frameworks (PyTorch preferred; JAX/HF a plus).
- Demonstrated ability to turn research concepts into working systems.
Normal Computing Corporation
New York · US · 98+ employees
Normal Computing Corporation is an applied AI company that develops AI foundations for complex enterprise workflows. The company focuses on enhancing AI reliability and reasoning, working at the intersection of probabilistic software infrastructure, hardware, and physics to solve challenging problems in semiconductors and industrial sectors.
