Applied AI Engineer - Silicon Co-design Group

NVIDIA NVIDIA · Semiconductors · Shanghai, China

NVIDIA is seeking an Applied AI Engineer to design, develop, and integrate AI/LLM-powered systems into their chip design and automation infrastructure. The role involves architecting and implementing solutions to enhance workflow efficiency, scalability, and intelligence, driving initiatives from concept to deployment. Requires hands-on experience building and deploying ML/AI systems or data-intensive backend services, with a focus on owning AI agents or LLM-powered workflows end-to-end.

What you'd actually do

  1. Designing and implementing AI/LLM-powered systems to improve post-silicon validation, automation, and workflow efficiency within semiconductor validation environments.
  2. Collaborating with multi-functional engineering teams to find opportunities for AI integration and performance optimization.
  3. Evaluating emerging frameworks, architectures, and tools to improve efficiencies powered by artificial intelligence across the organization.
  4. Establish and maintain data-driven indicators to quantify AI impact, identify performance gaps, and drive continuous improvement across systems.

Skills

Required

  • BS, MS, or PhD or equivalent experience in CS, EE, CE, or a related field
  • 5+ years of hands-on experience building and deploying ML/AI systems or data-intensive backend services
  • 2+ years of direct Applied AI experience independently owning an AI agent, LLM-powered workflow, or intelligent automation system end-to-end — from prototype through production deployment
  • Strong Python skills
  • proficiency in at least one static language such as C, C++, C#, Java, or Scala
  • Demonstrated experience with deep learning frameworks like PyTorch or TensorFlow
  • hands-on experience with agentic and orchestration tools including NeMo Agent Toolkit, LangChain, Semantic Kernel, AutoGen, CrewAI, or n8n
  • Proven track record with deploying, monitoring, and debugging scalable AI/ML models
  • Ability to balance multiple simultaneous projects
  • Excellent problem-solving, communication, and collaboration skills

Nice to have

  • Familiarity with modern AI technologies and methodologies for crafting and launching LLMs
  • Experience with building and deploying orchestration agents managing hundreds to thousands of tools
  • Ability to translate innovative AI research into practical, high-impact production tools
  • Experience working within a silicon development environment, with exposure to chip and system characterization methodologies

What the JD emphasized

  • independently owning an AI agent, LLM-powered workflow, or intelligent automation system end-to-end — from prototype through production deployment
  • building and deploying ML/AI systems or data-intensive backend services
  • deploying, monitoring, and debugging scalable AI/ML models
  • building and deploying orchestration agents managing hundreds to thousands of tools

Other signals

  • designing and implementing AI/LLM-powered systems
  • improving post-silicon validation, automation, and workflow efficiency
  • architect and implement solutions that enhance the efficiency, scalability, and intelligence of our workflows
  • driving initiatives from concept to deployment
  • hands-on experience building and deploying ML/AI systems or data-intensive backend services
  • direct Applied AI experience independently owning an AI agent, LLM-powered workflow, or intelligent automation system end-to-end — from prototype through production deployment