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. NVIDIA's CPU, GPU, and Tegra SoC products pass through this toolchain before production, and the group is rebuilding the toolchain around AI. 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 benefit teams, products, and silicon generations.
• Evaluate emerging AI frameworks and architectures and recommend technologies for adoption.
• Build data systems and quantitative indicators to measure AI impact, identify 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/artificial intelligence 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 deploying, monitoring, and debugging scalable AI/ML models.
• Strong electrical engineering fundamentals, including computer architecture, high-speed interfaces, timing, power basics, and firmware/driver structures and hardware interaction.
• Experience working within a silicon development environment, including exposure to chip and system characterization methodologies.
• Hands-on experience with silicon bring-up, characterization, or lab debugging using tools such as oscilloscopes, multimeters, and logic analyzers.
• Ability to balance multiple simultaneous projects, with strong problem-solving, communication, and collaboration skills.

Preferred Qualifications

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

Compensation and Benefits

• Level 3 base salary: $152,000–$241,500 USD per year.
• Level 4 base salary: $184,000–$287,500 USD per year.
• Eligibility for equity and benefits.
• Applications will be accepted at least until August 1, 2026.
• NVIDIA is an equal opportunity employer.