Senior AI Solutions Architect - Semiconductors

NVIDIA
Santa Clara
Workplace: OnsiteFull timeFunction: Solutions Engineering & Sales EngineeringExperience: 4+ yearsSkills: ["Python","C++","PyTorch","TensorFlow","CUDA","CUDA-X","Kubernetes","Docker","GitHub","EDA tools","Cadence","Synopsys","Siemens EDA","GPU","HPCl","CuLitho"]

Senior Solutions Architect to support NVIDIA’s semiconductor accounts by embedding NVIDIA accelerated computing, cuLitho, and AI into design, verification, and manufacturing workflows. You’ll partner with BD, Sales, and Developer Relations to accelerate EDA/CAD workflows, apply ML/DL to fab processes, and deliver technical demonstrations and trainings for customers.

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FursaFursa
NVIDIA
NVIDIA
2 months ago

Senior AI Solutions Architect - Semiconductors

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Source: Company careers pageValidated by: Fursa AI
Last checked: 15 hours agoStatus: Live

Job Summary

Senior Solutions Architect to support NVIDIA’s semiconductor accounts by embedding NVIDIA accelerated computing, cuLitho, and AI into design, verification, and manufacturing workflows. You’ll partner with BD, Sales, and Developer Relations to accelerate EDA/CAD workflows, apply ML/DL to fab processes, and deliver technical demonstrations and trainings for customers.
Location: Santa Clara
Workplace: Onsite
Employment Type: Full time
Job Function: Solutions Engineering & Sales Engineering
Seniority: Manager level

Key Responsibilities

  • •Support Business Development and Sales teams as part of a small Solutions Architecture team, partnering with Industry Business leads, Account Managers, and Developer Relations managers to drive ecosystem success across Semiconductor accounts.
  • •Work directly with EDA/CAD developers and customer design and manufacturing teams in a customer-facing setting.
  • •Help developers GPU-accelerate and scale EDA workflows — place-and-route, circuit simulation, timing and power analysis, DRC/LVS, and verification — and computational lithography (cuLitho).
  • •Apply ML/DL to semiconductor manufacturing: defect detection, inspection and metrology, yield optimization, and process control.
  • •Analyze EDA and manufacturing application architectures and find opportunities for acceleration.

Pay and Benefits

Equity and Bonus:Equity
Perks:Equity

Key Requirements

  • •MS/PhD in Electrical or Computer Engineering, Materials Science, Applied Physics, Computational Science, or related field (or equivalent experience)
  • •4+ years in semiconductor design, EDA, or semiconductor manufacturing and/or AI/ML applied to these domains
  • •Familiarity with EDA flows and tools (Cadence, Synopsys, Siemens EDA) and/or computational lithography, TCAD, or inspection/metrology systems
  • •Experience programming in Python and C/C++, with familiarity GPU-accelerating compute-intensive workloads
  • •Development experience with AI frameworks such as PyTorch or TensorFlow for vision, ML, or manufacturing use cases
Experience:4+ yearsSemiconductorsEDAAI/MLGPUHPC
Skills:PythonC++PyTorchTensorFlowCUDACUDA-XKubernetesDockerGitHubEDA toolsCadenceSynopsysSiemens EDAGPUHPClCuLitho
Languages:English
Tech Stack:PythonC++PyTorchTensorFlowCUDAKubernetesDockerGitHubEDA toolsCadenceSynopsysSiemens EDAGPUCUDA-X

Company Brief

NVIDIA
Designs and manufactures GPUs, AI accelerators, and system-on-chip products for gaming, data centers, professional visualization, and automotive markets, enabling advanced graphics, AI, and high-performance computing solutions worldwide.
Industry: Electronics Manufacturing
Company Size: Enterprise (1,001+ employees)
Revenue: USD 1B+
Growth: Public Company
Valuation: Public Company (Market Cap in USD)
Funding: IPO / Publicly Listed
Headquarters: Santa Clara, United States
Founded: 1993
Glassdoor
Glassdoor: 4.3
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