Senior Product Manager, Kubernetes AI Platform and Operational Tools

Reposted 15 Days Ago
Be an Early Applicant
2 Locations
In-Office
208K-380K Annually
Senior level
Artificial Intelligence • Computer Vision • Hardware • Robotics • Metaverse
The Role
Drive innovation for GPU clusters through platform management, identify gaps, develop projects, and engage with partners. Manage product roadmaps and self-service operations.
Summary Generated by Built In

NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It’s a unique legacy of innovation that’s fueled by great technology—and amazing people. Today, we’re tapping into the unlimited potential of AI to define 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.

NVIDIA operates one of the largest GPU computing fleets in the world, powering AI workloads across NVIDIA Cloud Partners and enterprise customers. Our Kubernetes AI Platform team is responsible for the platform layer that makes these GPU clusters operational at scale: cluster provisioning, runtime publication, self-service operations, and workload orchestration. We are looking for a product manager who wants to pioneer new platform technologies for AI infrastructure. In this role, you will identify gaps in how customers and partners operate GPU clusters at scale, develop new platform projects to fill them, and bring those innovations to market. You will also help NVIDIA develop its internal Kubernetes platform that powers innovation across the company. Have you built platform technologies that changed how teams operate infrastructure? Are you excited about developing new open-source projects at the intersection of Kubernetes and AI? We’d love to hear from you!

What We Need to See:

In this role, we will count on you to drive innovation for our partners, customers, and internal teams. Here is what that looks like:

  • Identify gaps in how customers and partners operate GPU clusters at scale and develop new projects to address their needs.

  • Bring internal platform innovations to market as open source software projects, including community strategy, contribution models, and ecosystem engagement.

  • Own the product roadmap for AI runtime generation, testing, packaging, and publication across cloud partners and deployment targets.

  • Drive platform-level cluster provisioning and lifecycle management across NVIDIA Cloud Partners and enterprise environments.

  • Own our self-service cluster operations surface: the APIs, control planes, and automation that let customers provision, upgrade, and run clusters independently.

  • Work directly with cloud partners and operators to translate their operational requirements into platform capabilities.

  • Partner with engineering on the architecture and delivery of Kubernetes operators, controllers, and platform services that support GPU-aware cluster behavior.

What We Need to See:

We are looking for someone who combines platform innovation instincts with the ability to ship infrastructure products. Specifically:

  • 12+ years of product management experience in Kubernetes platform engineering, cloud infrastructure, or GPU-accelerated compute environments.

  • Experience shipping Kubernetes platform products for hardware-aware compute environments.

  • Deep understanding of Kubernetes architecture: API server, scheduler, controller patterns, CRDs, device plugins, and operator frameworks.

  • Experience developing or leading open-source projects in the cloud-native or infrastructure space.

  • Track record defining multi-quarter strategy and leading execution with multiple engineering teams.

  • Experience working with cloud service providers or platform partners in a delivery or enablement capacity.

  • Bachelor's degree or equivalent experience in Business, Engineering, Computer Science, or a related field.

Ways to Stand Out from the Crowd:

We get especially passionate about candidates who bring experience in areas like these:

  • Crafting or leading open-source projects that gained meaningful community adoption.

  • AI/ML runtime lifecycle management, container image pipelines, or OCI distribution.

  • GPU scheduling, topology-aware placement, or multi-tenant GPU cluster management.

  • HPC workload orchestration in production environments.

  • Shipping platform products that partners or third-party operators depend on as well as contributions to Kubernetes SIGs, CNCF projects, or GPU-related open-source work.

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 plan your future, see what we can offer to you and your family 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 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 March 15, 2026.

This posting is for an existing vacancy. 

NVIDIA uses AI tools in its recruiting processes.

NVIDIA is committed to fostering a diverse 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.

Skills Required

  • 12+ years of product management experience in Kubernetes platform engineering, cloud infrastructure, or GPU-accelerated compute environments
  • Experience shipping Kubernetes platform products for hardware-aware compute environments
  • Deep understanding of Kubernetes architecture: API server, scheduler, controller patterns, CRDs, device plugins, and operator frameworks
  • Experience developing or leading open-source projects in the cloud-native or infrastructure space
  • Track record defining multi-quarter strategy and leading execution with multiple engineering teams
  • Experience working with cloud service providers or platform partners in a delivery or enablement capacity
  • Bachelor's degree or equivalent experience in Business, Engineering, Computer Science, or a related field

NVIDIA Compensation & Benefits Highlights

The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about NVIDIA and has not been reviewed or approved by NVIDIA.

  • Equity Value & Accessibility Equity awards and a discounted ESPP are highlighted as core parts of total compensation, enabling employees to share in the company’s success. Stock-based compensation and the two-year lookback ESPP are consistently described as especially valuable.
  • Healthcare Strength Health coverage is portrayed as robust, with comprehensive medical, dental, and vision options alongside mental health support and on-site care resources. Employer HSA contributions and wellness perks reinforce the depth of the offering.
  • Retirement Support Retirement programs are depicted as strong, featuring a meaningful 401(k) match with Roth options and support for Mega Backdoor Roth contributions. These elements position long-term savings as a notable advantage of the total rewards package.

NVIDIA Insights

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The Company
HQ: Santa Clara, CA
21,960 Employees
Year Founded: 1993

What We Do

NVIDIA’s invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing — with the GPU acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world. Today, NVIDIA is increasingly known as “the AI computing company.”

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