3 days ago
Base Salary
$224k - $357k/yr
Responsibilities
- Set technical direction, architecture, roadmaps, and long-term health for major platform areas.
- Lead infrastructure initiatives across team boundaries with firmware, hardware, and business partners.
- Own platform reliability by defining SLIs and SLOs, adding instrumentation, reducing MTTR, and automating incident response.
- Identify and deliver previously unaddressed automation opportunities.
- Architect AI-powered workflows that improve engineering productivity.
- Set technical standards through design reviews, technical writing, mentoring, and team guidance.
Requirements
- BS or MS degree in electrical engineering, computer science, or computer engineering, or equivalent experience.
- 12+ years of infrastructure, platform, DevOps, or SRE engineering experience.
- Deep expertise in CI/CD and test automation architecture, including pipeline design, build-system internals, caching, testing frameworks, and scaled-architecture failure modes.
- Strong Python fluency, infrastructure-as-code experience, and scripting ability.
- Experience with distributed systems, cloud or on-premises compute fleets, containers, and Kubernetes or equivalent orchestration.
- Strong understanding of database concepts, schema design, object modeling, and SQL or non-SQL databases.
- Previous ownership of cross-organizational production systems.
- Outstanding communication, leadership, teaching, technical writing, requirements, review, and mentoring skills.
- A history of growing other engineers formally or informally.
- Preferred experience writing technical proposals, design documents, or architecture decisions; using AI-assisted development tools; and developing device BIOS, firmware, or other low-level embedded software.
Benefits
- Eligible for equity and benefits.
- Applications accepted at least until October 26, 2026.
Tech Stack
Categories
About Nvidia
Nvidia designs and sells GPUs and accelerated computing platforms for data centers, AI/ML, graphics, gaming, and automotive, monetizing through hardware, software platforms (CUDA, AI frameworks), and systems like DGX and networking. Customers include cloud providers, enterprises, researchers, and OEMs. Founded in 1993 and headquartered in Santa Clara, it is a public company traded on NASDAQ under NVDA.