Applied AI Engineer

NVIDIA’s Silicon Co-Design Group is seeking an Applied AI Engineer to design and implement LLM-powered validation approaches and AI integrations across semiconductor design and automation workflows. The work centers on advancing post-silicon and validation processes from early concept stages through production deployment.

Responsibilities

• Design and deploy AI systems that improve the speed, intelligence, and scalability of post-silicon validation across semiconductor environments.
• Partner with multi-functional engineering teams across the organization to identify where AI can remove bottlenecks, and then build and deliver the solutions.
• Assess emerging AI frameworks and architectures early, before they become widely adopted across the industry.
• Build the data systems needed to validate outcomes, define quantitative measures of AI impact, close performance gaps, and support iterative improvement across the organization.

Requirements

• BS, MS, or PhD, or equivalent experience in CS, EE, CE, or a related field, plus 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 and proficiency in at least one static language such as C, C++, C#, Java, or Scala.
• Strong EE fundamentals, including computer architecture, high-speed interfaces, timing, power basics, and an understanding of firmware/driver structures and hardware interaction.
• Hands-on experience in production test, system validation, post-silicon bring-up, reliability, silicon debug, or silicon productization, including ATE, SLT, board-level test, validation, or yield analysis.
• Experience in a silicon development environment, including exposure to chip and system characterization methodologies, and familiarity with manufacturing and quality metrics such as yield, FPY, DPPM, RAS, TTR, and escape rate.
• Demonstrated ability to balance multiple concurrent projects, with strong problem-solving, communication, and teamwork skills.

Technology Stack

• Python; C; C++; C#; Java; Scala
• PyTorch; TensorFlow
• NeMo Agent Toolkit; LangChain; Semantic Kernel
• AutoGen; CrewAI; n8n

Compensation and Location

This role is based in California (hybrid) and offers an estimated USD 152,000 - 287,500 per year.

Benefits

• Eligibility for equity and benefits.
• Competitive salary.
• Generous benefits package.

How You Can Stand Out

• Experience with GPU, CPU, AI accelerator, networking, automotive, or other large-scale SoC programs.
• Familiarity with modern AI technologies and methodologies for crafting and launching LLMs.
• Experience building and deploying orchestration agents that manage hundreds to thousands of tools.
• Ability to translate AI research into practical, high-impact production tools.
• Hands-on experience with deep learning frameworks such as PyTorch or TensorFlow, including agentic and orchestration tools such as NeMo Agent Toolkit, LangChain, Semantic Kernel, AutoGen, CrewAI, or n8n.