Applied AI Engineer

Details

NVIDIA's Silicon Co-Design Group is seeking an Applied AI Engineer to innovate, develop, and integrate AI solutions into the design and automation infrastructure that powers its chips. Every CPU, GPU, and Tegra SoC NVIDIA has shipped in the past four years passed through this toolchain, with over 200 product SKUs optimized during the Blackwell generation alone. The team is rebuilding the toolchain around AI and is looking for an engineer to lead that effort.

The role involves architecting and implementing solutions that improve the efficiency, scalability, and intelligence of workflows, driving initiatives from concept through deployment.

Responsibilities

• Design and deploy LLM-powered validation pipelines that make post-silicon validation faster, smarter, and more scalable across semiconductor environments.
• Work with multifunctional engineering teams to identify opportunities where AI can eliminate friction and build solutions that have an impact across teams, products, and generations of silicon.
• Evaluate emerging AI frameworks and architectures, identify technologies worth adopting, and make the case for their adoption.
• Build data systems to measure AI impact, establish quantitative performance indicators, close performance gaps, and drive continuous improvement.

Requirements

• Bachelor's, master's, or doctoral degree, or equivalent experience, in computer science, electrical engineering, computer engineering, or a related field.
• At least 5 years of hands-on experience building and deploying machine learning or AI systems, or data-intensive backend services.
• At least 2 years of direct applied AI experience independently owning an AI agent, LLM-powered workflow, or intelligent automation system from prototype through production deployment.
• Strong Python skills and proficiency in at least one statically typed language such as C, C++, C#, Java, or Scala.
• Experience working in a silicon development environment, including exposure to chip and system characterization methodologies, process variation, statistical error rates, or advanced timing and power analysis.
• Hands-on experience with silicon bring-up, characterization, or lab debugging using tools such as oscilloscopes, multimeters, and logic analyzers.
• Strong electrical engineering fundamentals, including computer architecture, high-speed interfaces, timing, power basics, and firmware, driver, and hardware interaction structures.
• Ability to balance multiple concurrent projects, with excellent problem-solving, communication, and teamwork skills.

Preferred Qualifications

• Experience debugging complex system-level hardware/software interaction issues, including leading root-cause analysis of silicon or feature-level issues.
• Ability to translate innovative AI research into practical, high-impact production tools.
• 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.
• Experience with deep learning frameworks such as PyTorch or TensorFlow.
• Hands-on experience with agentic and orchestration tools including NeMo Agent Toolkit, LangChain, Semantic Kernel, AutoGen, CrewAI, or n8n.

Benefits

The position includes equity and benefits. NVIDIA offers a dynamic work environment and a generous benefits package.

Applications for this job will be accepted at least until August 1, 2026. NVIDIA is an equal opportunity employer.