Principal EDA R&D Engineer — AI‑Driven Formal Verification

NVIDIA Corporation; Austin (TX); On-site; USD 232,000 - 368,000; Full time

Benefits offered by this job

Equity

Benefits

Job summary

NVIDIA Corporation is seeking a Principal EDA R&D Engineer to pioneer next-gen hardware formal verification tools. You will lead research, architecture and development of core engines enhanced by Agentic AI frameworks and multi-agent systems to tackle multi-billion-gate builds.

You will translate research into production-grade EDA software, driving features from concept to release in a high-performance C/C++ environment, with a focus on scalability, optimization, and rigorous methods.

Qualifications

• Ph.D. or Master’s degree in CS/EE or related field.
• 15+ years of R&D experience building commercial or advanced academic EDA tools.
• Expert C/C++ development with memory optimization and multithreading.
• Experience with multi-agent AI pipelines and RTL languages.

Responsibilities

• Architect and advance formal verification algorithms such as BMC/IC3 and theorem proving.
• Develop multi-agent AI systems to analyze RTL topologies and tune solvers.
• Create orchestration layers for autonomous agents to handle large builds.
• Generate complex SVAs from natural language specs and architectural intent.
• Deliver production-grade EDA tools in high-performance C/C++ environments.

Skills

C/C++ (Modern C++17/20)

Multi-threading

Formal methods

Algorithm design

RTL languages knowledge

Education

Ph.D. or Master's in CS/EE

Tools

LangChain

AutoGen

CrewAI

SystemVerilog

Job description

NVIDIA Corporation is seeking a Principal EDA R&D Engineer to pioneer next-gen hardware formal verification tools. You will lead research, architecture and development of core engines enhanced by Agentic AI frameworks and multi-agent systems to tackle multi-billion-gate builds.

You will translate research into production-grade EDA software, driving features from concept to release in a high-performance C/C++ environment, with a focus on scalability, optimization, and rigorous methods.