Applied AI Engineer

About the role

NVIDIA's Silicon Co-Design Group is seeking an Applied AI Engineer to innovate, develop, and integrate innovative AI solutions into the design and automation infrastructure that powers our chips.

Responsibilities

• LLM-Powered Validation Pipelines: Design and deploy AI systems that make post-silicon validation faster, smarter, and more scalable across semiconductor environments.
• Work directly with multi-functional engineering teams across the organization to identify where AI can eliminate friction, and then build the solution. Your output will be felt across teams, products, and generations of silicon.
• Evaluate emerging AI frameworks and architectures before the rest of the industry catches on. Be the person who spots what's worth adopting, and make the case for it.
• Build the data systems that prove what's working. Establish clear, quantitative indicators of AI impact, close performance gaps, and drive iteration across the org to turn insight into lasting improvement!

Requirements

• BS, MS, or PhD or equivalent experience in CS, EE, CE, or a related field, with 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.
• Proven track record with deploying, monitoring, and debugging scalable AI/ML models.
• Strong EE fundamentals, including computer architecture, high-speed interfaces, timing, power basics, and a solid understanding of firmware/driver structures and hardware interaction.
• Experience working within a silicon development environment, with exposure to chip and system characterization methodologies.
• Hands-on experience with silicon bring-up, characterization, or lab debug using standard tools (e.g., oscilloscopes, multimeters, logic analyzers).
• Proven ability to balance multiple simultaneous projects with excellent problem-solving, communication, and collaboration skills.

Qualifications

• Familiarity with modern AI technologies and methodologies for crafting and launching LLMs with ability to translate innovative AI research into practical, high-impact production tools.
• Ability to translate innovative AI research into practical, high-impact production tools.
• Demonstrated experience with deep learning frameworks like PyTorch or TensorFlow, and hands-on experience with agentic and orchestration tools including NeMo Agent Toolkit, LangChain, Semantic Kernel, AutoGen, CrewAI, or n8n.
• Experience debugging complex system-level issues involving HW/SW interactions, including leadership or ownership in driving root cause analysis of silicon or feature-level issues.

Skills

• Deep technical expertise combined with a hands-on approach.
• Aim to push the boundaries of what's possible.

Benefits

• Your base salary will be determined based on your location, experience, and the pay of employees in similar positions.
• The base salary range is 152,000 USD - 241,500 USD for Level 3, and 184,000 USD - 287,500 USD for Level 4.
• You will also be eligible for equity and benefits.

Pay

• Your base salary will be determined based on your location, experience, and the pay of employees in similar positions.
• The base salary range is 152,000 USD - 241,500 USD for Level 3, and 184,000 USD - 287,500 USD for Level 4.

Schedule

• Full-time