Applied AI Engineer - Silicon Co-Design Group

NVIDIA
Shanghai
Workplace: OnsiteFull timeFunction: Data Science & Machine LearningExperience: 5+ yearsSkills: ["Problem-solving","Communication","Collaboration","Prioritization"]

Lead the design and deployment of AI/LLM-powered systems to enhance post-silicon validation and automation within NVIDIA’s silicon design toolchain. Collaborate with multi-disciplinary teams to integrate AI, evaluate new frameworks, and drive data-driven improvements across workflows and production deployments.

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FursaFursa
NVIDIA
NVIDIA
2 months ago

Applied AI Engineer - Silicon Co-Design Group

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Source: Company careers pageValidated by: Fursa AI
Last checked: 4 hours agoStatus: Live

Job Summary

Lead the design and deployment of AI/LLM-powered systems to enhance post-silicon validation and automation within NVIDIA’s silicon design toolchain. Collaborate with multi-disciplinary teams to integrate AI, evaluate new frameworks, and drive data-driven improvements across workflows and production deployments.
Location: Shanghai
Workplace: Onsite
Employment Type: Full time
Job Function: Data Science & Machine Learning

Key Responsibilities

  • •Design and implement AI/LLM-powered systems to improve post-silicon validation, automation, and workflow efficiency within semiconductor validation environments.
  • •Collaborate with multi-functional engineering teams to identify opportunities for AI integration and performance optimization.
  • •Evaluate emerging frameworks, architectures, and tools to improve efficiencies powered by AI across the organization.
  • •Establish and maintain data-driven indicators to quantify AI impact, identify performance gaps, and drive continuous improvement across systems.
  • •Lead the integration and evolution of the AI-driven toolchain powering NVIDIA’s silicon design processes from concept to production deployment.

Key Requirements

  • •5+ years of hands-on experience building and deploying ML/AI systems or data-intensive backend services in CS/EE/CE or related fields.
  • •2+ years of direct Applied AI experience owning an AI agent, LLM-powered workflow, or intelligent automation system end-to-end—from prototype through production deployment.
  • •Strong Python skills and proficiency in at least one static language such as C, C++, C#, Java, or Scala.
  • •Experience with deep learning frameworks like PyTorch or TensorFlow, and hands-on experience with agentic/orchestration tools such as NeMo Agent Toolkit, LangChain, Semantic Kernel, AutoGen, CrewAI, or n8n.
  • •Proven track record deploying, monitoring, and debugging scalable AI/ML models and balancing multiple projects.
Experience:5+ yearsSemiconductorAI/MLAccelerated computing
Education:
Skills:Problem-solvingCommunicationCollaborationPrioritization
Tech Stack:PythonCC++C#JavaScalaPyTorchTensorFlowLangChainNeMoSemantic KernelAutoGenCrewAIN8n

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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