Senior Platform AI Engineer

NVIDIA•Santa Clara, CA

4d•$184,000 - $356,500•Hybrid

About The Position

NVIDIA's Silicon Co-Design Group (SCG) is seeking Senior AI Platform Engineers. They will set the technical direction and lead the end-to-end delivery of the efficiency platform that supports our intelligent automation ecosystem. If you are energized by building foundational platforms at the intersection of ML infrastructure and large-scale systems, this is your opportunity! The platform you architect will run every workflow involving NVIDIA silicon — from bring-up, characterization, and debug to production sign-off. If leading the foundation that the next generation of SCG engineers builds on is the problem you want to solve, we'd like to talk!

Requirements

BS, MS, or PhD or equivalent experience in CS, EE, CE, or a related field, with 8+ years of hands-on experience designing and operating production-grade platform or backend infrastructure.
5+ years of direct ML infrastructure experience, including end-to-end ownership of a model serving platform or latency-sensitive backend service from initial architecture through sustained production operation.
Demonstrated track record of setting technical direction at the department or company level: defining platform strategy, establishing architectural standards, and leading initiatives spanning multiple teams.
Strong Python skills and proficiency in at least one compiled language such as C, C++, Go, Java, or Rust.
Hands-on experience with job queues + sandboxed execution (Kubernetes Jobs, Celery/Sidekiq/Temporal, container runtimes with resource isolation).
Strong communication and leadership skills, with the ability to align senior team members and drive architectural decisions across organizations with contending priorities.

Nice To Haves

Industry recognition in ML infrastructure or distributed systems — through publications, conference talks, open-source contributions, or technical leadership visible beyond your current organization.
Experience driving platform architecture at company scale, including engineering standards or frameworks broadly adopted by other teams.
Exposure to silicon design, methodology, validation or EDA toolchains, especially the cadence of chip development lifecycles.
Experience building or operating AI platforms within a silicon development, validation or EDA environment, with a firsthand understanding of the reliability and scale demands of chip design toolchains.
Track record of mentoring senior engineers and growing technical talent — shaping the capabilities of the team as much as the platform itself.

Responsibilities

Define the architectural direction, infrastructure investments, and roadmap priorities for the efficiency platform — across silicon architecture, build, methodology, validation, and applied AI teams.
Define platform contracts and onboard new agents and skills from the domain teams across SCG building on the platform.
Owning end-to-end delivery of the platform — from design and implementation through sustained production operation — with accountability for security, reliability, performance, and evolution.
Leading the unified solutions including orchestration patterns, authentication and authorization, observability, and SLA enforcement.
Driving platform-wide decisions with multi-functional impact.
Managing storage and caching strategies that scale across heterogeneous compute environments.
Serving as the technical authority for infrastructure powered by artificial intelligence across SCG: setting engineering standards, resolving cross-team architectural challenges, and mentoring senior engineers.