Description
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 their chips.
Every CPU, GPU, and Tegra SoC NVIDIA has shipped in the past four years passed through their toolchain on its way to production , over 200 product SKUs were optimized during the Blackwell generation alone. Now they're rebuilding that toolchain around AI, and they're looking for the engineer to lead that charge.
In this role, you will architect and implement solutions that enhance the efficiency, scalability, and intelligence of their workflows, driving initiatives from concept to deployment.
Responsibilities
- LLM-Powered Validation Pipelines: Design and deploy AI systems that make post-silicon validation faster, smarter, and more scalable across semiconductor environments.
- Cross-Team AI Integration: Work directly with multi-functional engineering teams across the organization to identify where AI can eliminate friction, and then build the solution.
- Technology Scouting & Evaluation: Evaluate emerging AI frameworks and architectures before the rest of the industry catches on.
- Impact Measurement & Continuous Improvement: Build the data systems that prove what's working.
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.
Benefits
You will also be eligible for equity and benefits.
Applications for this job will be accepted at least until August 1, 2026.