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Product Engineer, Developer Platform

NVIDIA2,503 open roles

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US CA Santa Clara
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Your applicationOpen nowProduct Engineer, Developer PlatformNVIDIA · US CA Santa Clara
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The clock on this job

Early applications get read.

8.2% of postings close within 7 days. Measured by our own scanner across the market. NVIDIA postings stay open a median of 27 days.

Share of postings closed within
  1. 1.8%1 day
  2. 3.8%3 days
  3. 8.2%7 days
  4. 15.2%14 days
  5. 34.2%30 days
This job: posted today

NVIDIA median: 27 days open

The posting

For more than 25 years, NVIDIA has driven innovation in computer graphics, PC gaming, and accelerated computing. It’s a unique legacy of innovation that’s fueled by great technology—and amazing people. Today, we’re harnessing the boundless possibilities of AI to build the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what’s never been done before takes vision, innovation, and the world’s best talent. As an NVIDIAN, you’ll be immersed in a diverse, supportive environment where everyone is inspired to do their best work. Come join the team and see how you can make a lasting impact on the world.

DSX OS is NVIDIA's open source foundation for AI infrastructure. It is a growing portfolio of engineering teams building in the open. Every project in that portfolio needs to meet a shared bar for open-source readiness: code hygiene, governance, community health. Today, that's measured by hand, project by project. This role owns an internal product that changes that to a platform that scores, tracks, and reports on readiness across the DSX OS portfolio, and the roadmap that takes it from an internal utility to the definition of what "open source ready" means for DSX OS.

What you'll be doing:

  • Lead the platform as production infrastructure. Maintain, harden, and evolve it from a measurement tool into the system every DSX OS project runs on — reliability and data quality matter because everything else in the program depends on it.
  • Automate scoring. Replace manual review-fix-recheck loops with tooling, so the portfolio scales through automation instead of added effort. Self-serve integration.
  • Build scoring into onboarding and workshop experiences. This lets participants get real-time feedback on their own project instead of waiting for manual review. It increases how many teams a single event can support.
  • Engineering team feedback loop. Work directly with the project teams using the platform, capture friction signals, and feed them back into the product instead of letting issues pile up in a backlog.
  • Readiness tracking and reporting. Automate the generation and tracking of per-project readiness plans so status, blockers, and progress are transparent to leadership without manual assembly.

What we need to see:

  • 8+ years of relevant experience and a bachelors degree (or equivalent experience)
  • Experience leading a software product or internal platform end-to-end and making the calls on what gets built, why, and in what order
  • Strong software engineering skills, with a track record of turning manual, error-prone processes into reliable automation
  • Hands-on experience with agentic coding tools (e.g., Claude Code, Copilot, Cursor) as part of your actual engineering workflow, not just casual use
  • Experience running a production system in the real world — on-call, incident response, or otherwise owning uptime and reliability for something people depend on daily
  • Experience building reporting or dashboards that a non-engineering audience (leadership, partners) can trust as a source of truth
  • Ownership mentality for production systems — system dependability and integrity of data fall under your responsibility, not someone else 's

Ways to stand out from the crowd:

  • Built or operated a rubric-based scoring or compliance system — quality gates, readiness checks, policy-as-code — where the output has to be defensible enough for people to act on it
  • Experience using LLMs within an evaluation pipeline (LLM-as-judge, qualitative signal assessment at scale) rather than only deterministic pass/fail checks
  • Designed a metric or signal taxonomy from scratch — deciding what to measure, how to weight it, and how to keep a single score relevant as the system it measures evolves
  • Built a tool that abstracts over multiple backends or platforms (e.g., supporting both GitHub and GitLab) so it isn't locked to one provider's API
  • Experience with GitOps-style automation — automated checks that run against every repo or PR or equivalent experience without a human in the loop

Widely considered to be one of the technology world’s most desirable employers, NVIDIA offers highly competitive salaries and a comprehensive benefits package. As you consider your future, explore what we can provide for you and your family at www.nvidiabenefits.com/

Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 168,000 USD - 270,250 USD.

You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until October 12, 2026.

This posting is for an existing vacancy.

NVIDIA uses AI tools in its recruiting processes.

NVIDIA is committed to fostering an inclusive work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.

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