Note: The job is a remote job and is open to candidates in USA. NVIDIA is a technology company focused on computer graphics, gaming, accelerated computing, and artificial intelligence. The Senior Platform AI Engineer will set the technical direction and lead end-to-end delivery of an efficiency platform supporting an intelligent automation ecosystem, including architecture, infrastructure, orchestration, security, reliability, observability, and production operations. The role also serves as a technical authority, drives cross-functional architectural decisions, and mentors senior engineers.
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
Skills
- 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
- 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
Benefits
- NVIDIA delivers a comprehensive benefits package.
- You will also be eligible for equity.
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