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NVIDIA

Designs the chips and software that power AI

Senior Physical Design AI Engineer

AI Application EngineeringConfirmed live in the last 24 hours
Full-timeBengaluru, Karnataka, IndiaNo salary listedHybrid

About the Job

Requirements

  • At least 4 years of experience in Physical Design, with a BE/BTech/MTech degree or equivalent experience.
  • Strong understanding of the RTL-to-GDSII flow and design implementation in leading process technologies, including synthesis, place and route, clock tree synthesis, timing convergence, and layout closure.
  • Good understanding of AI concepts such as tokens, KV cache, context windows, skills, agents, subagents, and hooks.
  • Hands-on experience with AI tools such as Claude, Codex, and Cursor.
  • Strong knowledge and experience in standard place-and-route flows.
  • Good automation skills in Tcl, Python, and tool-specific scripting for one or more industry-leading place-and-route tools.
  • Ability to multitask and work effectively in a global environment.
  • Excellent communication skills, strong motivation, and strong analytical and problem-solving abilities.

Responsibilities

  • Work with Physical Design Implementation teams to understand complex problems and build agentic AI solutions for all product lines.
  • Deliver efficient, token-optimized AI solutions that consistently produce high-quality outputs.
  • Provide continuous support, maintenance, and enhancements for AI solutions.
  • Benchmark solutions across various AI models to evaluate and improve their effectiveness.
  • Research and innovate new AI methods to address evolving physical design challenges.
  • Build robust regression testbenches to validate the quality, reliability, and performance of AI solutions.

Desired Qualifications

  • Experience with Synopsys ICC2 and Cadence Innovus flows is preferred.

About the Company

NVIDIA

Designs the chips and software that power AI

NVIDIA designs the chips and software that power artificial intelligence and sells complete data center systems to cloud providers, AI labs, and other businesses, along with GeForce graphics cards for gamers. Its GPUs, chips that perform thousands of calculations at once, became the main hardware for AI after researchers used them to train the AlexNet image-recognition model in 2012. NVIDIA connects many GPUs with its own processors and networking gear into servers and rack-sized computers, and developers program them through its CUDA software. These systems bring in most of its sales, and it also makes chips for cars and robots. Jensen Huang co-founded NVIDIA in 1993, and it is based in Santa Clara, California.

Company size
10,001+
Company stage
IPO
Headquarters
Santa Clara, CA
Founded
1993

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