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Job Description
Structured overview of role & requirementsAbout This Role
Develop and maintain AI-driven solutions to improve Physical Design Implementation efficiency and quality across NVIDIA product lines.
Collaborate with domain experts to understand complex implementation challenges and deliver agentic AI tools adapted to RTL-to-GDSII physical design flows.
Benchmark, validate, and innovate AI methods addressing problems in synthesis, place and route, and layout closure workflows.
Minimum Requirements
4+ years of experience in Physical Design with BE/BTech/MTech or equivalent experience.
Strong understanding of RTL-to-GDSII flow and design implementation including synthesis, place and route, clock tree synthesis, and timing closure.
Hands-on knowledge of AI concepts (tokens, KV cache, context windows, agents) and AI tools (Claude, Codex, Cursor).
Automation skills in Tcl, Python, and scripting for industry-leading place-and-route tools; experience with Synopsys ICC2 and Cadence Innovus preferred.
Ideal Candidate Profile
Experienced in standard place-and-route flows within leading process technologies to develop scalable AI solutions.
Able to integrate AI technologies effectively into physical design workflows with a focus on improving productivity and quality.
Skilled at building robust regression testbenches and benchmarking AI models to ensure reliability and performance of solutions in a global team environment.