Top Tech Jobs & Startup Jobs

Lead validation of ML datacenter stacks from cluster to rack scale for CSPs: define test strategies, reproduce and triage customer bugs, validate fixes, run perf benchmarks, manage test data and tooling, produce release-readiness reports, and collaborate with internal and partner engineering teams.

Serve as the embedded systems expert for NVIDIA Physical AI partners, integrating sensors, deploying and optimizing robotics foundation models on Jetson-class edge hardware, guiding customers from prototype to production, and delivering reference implementations and workshops.

Serve as a strategic compensation advisor to global recruiting, HRBPs, and business leaders. Provide analysis and recommendations for offers, promotions, transfers, and retention; improve comp programs, policies, and processes; implement ongoing comp programs and respond to comp-related inquiries.

Work with architects, hardware, firmware, and test teams to co-design and verify system-level speed and reliability features. Develop verification collateral, automation and AI/LLM-assisted tooling, perform pre- and post-silicon characterization and tester-to-system correlation, and lead debug of complex silicon issues to ensure on-time product shipment.

Lead end-to-end lifecycle of silicon-based products: plan, manage milestones, and ramp to mass production. Coordinate engineering, design, and marketing; own technical requirements, datasheets, and feature prioritization. Track progress, mitigate risks, report to senior leadership, and drive process improvements to ensure timely, on-budget delivery.

Provide onsite and remote technical support for NVIDIA Ethernet and AI infrastructure, troubleshoot Linux-based systems, debug networking and interoperability issues, collaborate with engineering and marketing, document support methodologies, and act as primary customer contact, spending at least one week per month onsite.

Lead product marketing for NVIDIACUDA and core acceleration libraries. Own positioning, messaging, and go-to-market for libraries and AI frameworks, translate technical features into developer-focused narratives, and build AI-driven PMM automation and assets.

Lead technical programs with hyperscalers and OEM/ODMs to deliver AI datacenter infrastructure from design through production. Define schedules and milestones, translate customer requirements into cross-functional plans, resolve issues, manage qualification/validation, monitor factory production and yields, and communicate program health to customers and leadership. Champion post-deployment sustaining support and coordinate global teams to ensure timely delivery and customer acceptance.

Design and implement CUDA Tile compiler transformations, MLIR dialects, lowering passes, and optimization techniques for NVIDIA GPUs. Optimize tile-based kernel performance across GPU generations, define public APIs, conduct performance analysis, and develop robust software, tests, and debugging workflows. The role requires independent project ownership and collaboration within a product-focused engineering team.

Lead technical engagements with cloud service providers on rack-scale system software and firmware. Drive architecture alignment, integration readiness, error handling and recovery, health telemetry, firmware orchestration, and serviceability. Capture CSP feedback, influence NVIDIA system software design, improve tooling and tests, and mitigate execution risks through early collaboration.