NVIDIA Logo

NVIDIA

Technical Product Manager - AI Infra Resilience

Reposted Yesterday
Be an Early Applicant
Hybrid
Santa Clara, CA, USA
208K-380K Annually
Expert/Leader
Hybrid
Santa Clara, CA, USA
208K-380K Annually
Expert/Leader
Own the roadmap and delivery of AI infrastructure resilience platform features, including telemetry, health checks, attribution, observability APIs, and deployment experiences. Translate developer needs into product strategy, collaborate with engineering on architecture and execution, engage open-source contributors through GitHub, and align product, marketing, field, and engineering teams. The role requires deep technical expertise in AI infrastructure, Kubernetes, developer platforms, or related systems, plus extensive product management or engineering experience.
The summary above was generated by AI

GPU clusters fail. Workloads crash at 3am, AI teams file tickets pointing at hardware, hardware teams point back at software, and the actual cause stays unknown until someone with deep enough context digs through DCGM metrics, XID history, and NCCL traces. That forensics work shouldn't fall to a human on-call every time. We're building the platform that automates it, and we need a PM who has been that on-call engineer.


We're hiring a Senior Product Manager to own workload failure attribution: how a GPU cluster figures out whether a failed job was caused by hardware, system software, or application code, and how that verdict gets surfaced to operators, schedulers, and the open source developer surface built on top of it. You will own the roadmap and work directly with the engineering and operations communities who deploy and extend this platform. This role is part of NVIDIA's DSX Platform, NVIDIA's open, modular infrastructure software for designing, operating, and optimizing AI factories at scale. No prior product management title required. If you are a deeply technical product manager, architect, SRE, or infra engineer who has lived the GPU cluster failure-triage problem, we want to hear from you.


What You'll Be Doing:

  • Drive the product vision, roadmap, and delivery for workload failure attribution, in close collaboration with engineering on architecture and prioritization.
  • Identify gaps in how customers and partners triage GPU cluster failures at scale and define new attribution capabilities to close them, including how an NCCL timeout gets attributed to hardware, system software, or application, and which signals belong in a public API vs. an entitled runtime extension.
  • Work directly with cloud partners and cluster operators to translate their operational triage requirements into platform capabilities.
  • Drive community engagement strategy for the open source attribution project, including contribution models, ecosystem partnerships, and developer adoption.

What We Need To See:

  • 12+ years total experience.
  • 5+ years in product management, solutions architecture, software engineering, or site reliability engineering on technical infrastructure products. Technical depth on GPU or AI infra is required.
  • Familiarity with GPU failure modes: XID codes, ECC correctable and uncorrectable errors, DCGM metrics, NVLink and PCIe health signals.
  • Technical understanding of why AI workloads fail: GPU hardware failure modes, distributed training failure patterns (NCCL timeouts, framework errors, hardware vs. system software vs. application fault distinction), and the telemetry systems (DCGM, sysfs, dmesg) that surface these signals.
  • Demonstrated ability to work with senior technical customers and translate operational requirements into product decisions.
  • Strong written and verbal communication across technical and non-technical audiences.
  • Bachelor's degree in Computer Science or equivalent experience.

Ways To Stand Out From The Crowd:

  • Former SRE or infra engineer on GPU clusters. You have triaged job failures, parsed XID logs, and understand the cross-team deep dives that happen when a multi-thousand-GPU training run fails.
  • Deep familiarity with GPU scheduling, topology-aware placement, or multi-tenant GPU cluster management: Slurm prolog/epilog, Kueue, or Kubernetes-native scheduler environments.
  • Experience building products that produce structured diagnostics or attribution output: health verdict schemas, log analysis pipelines, rules-engine systems, or observability APIs at data center scale.
  • Practical experience delivering or contributing to an open-source infrastructure project, including managing contributor engagement on GitHub.

NVIDIA is widely considered one of the technology world’s most desirable employers. We have some of the world's most forward-thinking and hardworking people on our team. If you're creative and autonomous, we want to hear from you!


#LI-Hybrid

Your base salary will be determined based on your location, experience, and other objective job-related factors. The expected base salary ranges for this position are:
208,000 USD – 327,750 USD for Level 5; and 240,000 USD – 379,500 USD for Level 6.

You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until November 7, 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.

HQ

NVIDIA Santa Clara, California, USA Office

2701 San Tomas Expressway, Santa Clara, CA, United States, Santa Clara

NVIDIA San Francisco, California, USA Office

San Francisco, United States

NVIDIA San Jose, California, USA Office

San Jose, United States

Similar Jobs

6 Minutes Ago
Easy Apply
Remote or Hybrid
United States
Easy Apply
227K-272K Annually
Expert/Leader
227K-272K Annually
Expert/Leader
eCommerce • Healthtech • Kids + Family • Retail • Social Media
Own and evolve AWS infrastructure, Kubernetes, Terraform, CI/CD, developer tooling, observability, security defaults, backup recovery, and incident response. Build reliable automation and self-service workflows, establish SLOs and actionable alerting, support engineers across environments, lead platform initiatives, improve security and reliability practices, and mentor engineers serving millions of users.
Top Skills: Amazon EksAmazon RdsAWSCircleCICronitorDatadogGithub ActionsKubernetesMySQLPagerdutyRedisRubyRuby On RailsSentrySidekiqTerraform
10 Minutes Ago
Remote or Hybrid
US
89K-110K Annually
Entry level
89K-110K Annually
Entry level
HR Tech • Information Technology • Professional Services • Sales • Software
Manage a portfolio of mid-market SaaS accounts focused on product adoption, usage, retention, and customer satisfaction. Build account relationship frameworks, conduct status calls and business reviews, maintain account plans, assess customer health, mitigate churn, and identify growth opportunities. Act as a trusted advisor and customer advocate while collaborating with Product, Development, Marketing, and Sales. Meet net retention and CSAT/NPS goals through data-driven planning and execution.
Top Skills: AsanaChurnzeroHrisSaaSSalesforce
18 Minutes Ago
In-Office or Remote
Site of Old Bullion, NV, USA
215K-358K Annually
Expert/Leader
215K-358K Annually
Expert/Leader
Artificial Intelligence • Healthtech • Machine Learning • Natural Language Processing • Biotech • Pharmaceutical
Leads Pfizer Oncology account marketing strategy, planning, commercialization, stakeholder alignment, field engagement, promotional execution, budgets, and GPO marketing plans. Advises senior leadership on policies, risks, opportunities, and strategic priorities while managing cross-functional teams and multiple portfolio assets. Requires extensive pharmaceutical commercial experience, oncology account expertise, strategic and analytical skills, leadership capability, compliance focus, and success in matrixed environments.

What you need to know about the San Francisco Tech Scene

San Francisco and the surrounding Bay Area attracts more startup funding than any other region in the world. Home to Stanford University and UC Berkeley, leading VC firms and several of the world’s most valuable companies, the Bay Area is the place to go for anyone looking to make it big in the tech industry. That said, San Francisco has a lot to offer beyond technology thanks to a thriving art and music scene, excellent food and a short drive to several of the country’s most beautiful recreational areas.

Key Facts About San Francisco Tech

  • Number of Tech Workers: 365,500; 13.9% of overall workforce (2024 CompTIA survey)
  • Major Tech Employers: Google, Apple, Salesforce, Meta
  • Key Industries: Artificial intelligence, cloud computing, fintech, consumer technology, software
  • Funding Landscape: $50.5 billion in venture capital funding in 2024 (Pitchbook)
  • Notable Investors: Sequoia Capital, Andreessen Horowitz, Bessemer Venture Partners, Greylock Partners, Khosla Ventures, Kleiner Perkins
  • Research Centers and Universities: Stanford University; University of California, Berkeley; University of San Francisco; Santa Clara University; Ames Research Center; Center for AI Safety; California Institute for Regenerative Medicine

Sign up now Access later

Create Free Account

Please log in or sign up to report this job.

Create Free Account