Senior AI Engineer - Silicon Toolchain for Production

NVIDIA Corporation; Santa Clara, Northern (CA, KY); Hybrid; USD 184,000 - 357,000; Full time

Benefits offered by this job

Equity

Benefits

Job summary

NVIDIA is recruiting for a senior engineer in the Silicon Co-Design Group in California to lead the rebuild of our toolchain around AI. You will work at the intersection of silicon, firmware, and productization, shaping the next generation of NVIDIA's silicon products.

You will simulate power-controller interactions, deploy production Python services and LLM-backed pipelines, and mentor a team of engineers to push performance and AI capabilities while collaborating across hardware and software

Qualifications

• BS or MS in EE/CE/CS with 8+ years in silicon bringup, firmware, or productization.
• Experience deploying production Python services and data pipelines, including an LLM-backed system.
• Ability to read silicon characterization outputs and weigh tradeoffs.
• Ability to evaluate new AI tooling within a week of release and stay updated.

Responsibilities

• Simulate power controller interactions, voltage-frequency points, and binning yields.
• Build systems to push performance and power efficiency toward the speed of light.
• Translate silicon/firmware behavior into engineering context.
• Break down silicon product optimization workflows into composable skills and orchestration layers.
• Lead eval-driven development for AI in production and CI regression gates.
• Mentor engineers and shape the team's AI direction.

Skills

Python

LLM-backed systems

Data pipelines

Silicon bring-up

Firmware experience

Education

BS or MS in EE/CE/CS

Tools

CI/CD

Tracing/Monitoring

Job description

NVIDIA is recruiting for a senior engineer in the Silicon Co-Design Group in California to lead the rebuild of our toolchain around AI. You will work at the intersection of silicon, firmware, and productization, shaping the next generation of NVIDIA's silicon products.

You will simulate power-controller interactions, deploy production Python services and LLM-backed pipelines, and mentor a team of engineers to push performance and AI capabilities while collaborating across hardware and software