Senior AI Solutions Architect

What you'll do

• Act as a technical advisor to EDA/CAD developers and customer engineering teams to embed NVIDIA accelerated computing into workflows.
• Partner with sales and business development teams to drive ecosystem success across semiconductor accounts.
• Help developers GPU-accelerate and scale EDA workflows including place-and-route, circuit simulation, and verification.
• Apply ML/DL to semiconductor manufacturing for defect detection, inspection, metrology, and yield optimization.
• Analyze EDA and manufacturing application architectures to identify specific opportunities for hardware acceleration.
• Provide technical feedback to internal engineering, product, and research teams.
• Deliver trainings, hackathons, and technical demonstrations on NVIDIA solutions and platforms.

What we're looking for

• MS/PhD in Electrical or Computer Engineering, Materials Science, Applied Physics, Computational Science, or a related technical field (or equivalent experience).
• 4+ years in semiconductor design, EDA, or semiconductor manufacturing, including chip design, verification, TCAD, lithography, or fab process/yield engineering.
• Experience in AI/ML applied to semiconductor domains, including defect detection, inspection, metrology, yield optimization, and process control.
• Familiarity with EDA flows and tools such as Cadence, Synopsys, or Siemens EDA, and/or computational lithography, TCAD, or inspection/metrology systems.
• Experience in algorithm programming using Python and C/C++ with familiarity GPU-accelerating compute-intensive workloads.
• Development experience using major AI frameworks like PyTorch or TensorFlow for vision, ML, or manufacturing use cases.
• Familiarity with accelerated computing platforms, GPU-based distributed systems, HPC clusters, containers, numerical libraries, and version control.
• Experience with CUDA, CUDA-X, Kubernetes, or PCIe accelerators such as GPUs and FPGAs (preferred).