Senior Manager, AI and HPC Cluster Engineering Enablement

Posted Yesterday
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6 Locations
In-Office or Remote
272K-489K Annually
Senior level
Artificial Intelligence • Computer Vision • Hardware • Robotics • Metaverse
The Role
Leads engineering enablement for large-scale AI/HPC clusters, managing a support team, training and documentation, request intake and prioritization, specialist debugging coordination, and user community development. Partners across architecture, software, firmware, networking, storage, datacenter operations, performance, and program teams. Uses service metrics and user feedback to improve workflows, self-service guidance, resource allocation, and support quality.
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 an inclusive, 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 is reshaping accelerated computing and AI infrastructure with advancements in GPUs, networking, software, and large-scale datacenter platforms. We seek a senior engineering manager to support our internal engineers in adopting next-generation AI/HPC clusters as they transition from initial setup to wider usage.


Within Applied Systems Engineering, you will be responsible for cluster engineering support by growing the engineering community, creating hands-on training, and handling requests from engineering users and supporting teams. You will set up clear processes for intake, prioritization, ownership, and communication for requests. These will include onboarding, workload help, and access to experts for in-depth debugging. Your knowledge of large-scale infrastructure will enable you to identify needs, coordinate resources, and ensure progress on requests.


You will partner with architecture, bringup, software, firmware, networking, storage, datacenter operations, performance, and program teams. The ideal candidate brings engineering leadership and operational experience in Linux-based HPC/AI environments. They excel at developing people, managing competing requests, and converting technical knowledge into effective training and support.


What you'll be doing:
  • Lead and grow a team dedicated to cluster engineering support, community involvement, training, and managing engineering requests.
  • Develop a connected internal engineering community through onboarding, office hours, technical workshops, and knowledge sharing that help users work effectively on evolving AI/HPC platforms.
  • Create practical training and documentation for cluster access, workload submission, GPU resource scheduling, shared storage, operational procedures, and submitting actionable support requests.
  • Own the request intake and prioritization process: clarify the need, capture impact and priorities, identify dependencies, and maintain a transparent queue aligned with engineering achievements and available capacity.
  • Coordinate requests that require specialist investigation, including deep-debug support. Connect requesters with the appropriate technical owners, agree on next steps, track progress, and bring up stalled requests.
  • Partner with cluster operations and engineering teams on access, allocations, maintenance communications, and resource needs so users can plan and complete their work.
  • Turn recurring questions, request patterns, and specialist findings into reusable guidance, training, and proposals for self-service tools or workflow improvements.
  • Use request volume, response time, aging, completion trends, training participation, and user feedback to improve support quality and communicate priorities and capacity needs.
What we need to see:
  • BS, MS, or PhD in Computer Science, Computer Engineering, Electrical Engineering, Applied Science, or equivalent practical experience.
  • 8+ years of experience in high-performance computing, AI infrastructure, datacenter systems, production engineering, or large-scale Linux environments.
  • 5+ years of technical leadership or engineering management experience, including mentoring engineers, setting priorities, and delivering across organizational boundaries.
  • Practical understanding of Linux clusters, GPU workload scheduling, cluster management, networking, servers, and large-scale shared storage, with the ability to understand technical requests and engage the right specialists.
  • Experience coordinating engineering requests, support queues, or operational workflows, including prioritization, ownership, managing blocking issues, and communication through completion.
  • Ability to translate complex infrastructure concepts into clear documentation, training, and guidance for engineers with different levels of experience.
  • Strong collaboration and communication skills, with sound judgment when balancing user needs, engineering priorities, and resource constraints in an evolving hardware and software environment

.

Ways to stand out from the crowd:
  • Experience designing or operating large HPC/AI clusters and supporting the engineers who depend on them, especially during early hardware, firmware, or software lifecycle phases.
  • Experience with cluster management platforms and workload schedulers, GPU resource allocation, and large or petabyte-scale filesystems.
  • Established success in forming engineering communities, induction programs, technical workshops, or peer learning activities that increase user self-sufficiency and performance.
  • Experience improving request workflows across compute, networking, storage, and software teams, with clear handoffs, shared priorities, and measurable service improvements.
  • Proven experience in developing inclusive teams that foster ownership, knowledge transfer, thoughtful decision-making, and career growth.

NVIDIA is leading the way in groundbreaking developments in Artificial Intelligence, High-Performance Computing, and Visualization. Our invention serves as the visual cortex of modern computers and is at the heart of our products and services. Our work opens up new universes to explore, enables amazing creativity and discovery, and powers what were once science fiction inventions from artificial intelligence to autonomous cars. NVIDIA is seeking exceptional individuals like you to help us drive the next wave of artificial intelligence.


NVIDIA is considered one of the technology world’s most desirable employers. We have some of the most forward-thinking and hardworking people on the planet working for us. If you are creative and autonomous, we want to hear from you!

Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 272,000 USD - 431,250 USD for Level 4, and 320,000 USD - 488,750 USD for Level 5.

You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until October 31, 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.

Skills Required

  • BS, MS, or PhD in Computer Science, Computer Engineering, Electrical Engineering, Applied Science, or equivalent practical experience
  • 8+ years of experience in high-performance computing, AI infrastructure, datacenter systems, production engineering, or large-scale Linux environments
  • 5+ years of technical leadership or engineering management experience, including mentoring engineers, setting priorities, and delivering across organizational boundaries
  • Practical understanding of Linux clusters, GPU workload scheduling, cluster management, networking, servers, and large-scale shared storage
  • Experience coordinating engineering requests, support queues, or operational workflows, including prioritization, ownership, blocking issues, and communication through completion
  • Ability to translate complex infrastructure concepts into clear documentation, training, and guidance for engineers with different experience levels
  • Strong collaboration and communication skills, with sound judgment when balancing user needs, engineering priorities, and resource constraints
  • Experience designing or operating large HPC/AI clusters and supporting engineers during early hardware, firmware, or software lifecycle phases
  • Experience with cluster management platforms, workload schedulers, GPU resource allocation, and large or petabyte-scale filesystems
  • Experience forming engineering communities, induction programs, technical workshops, or peer learning activities
  • Experience improving request workflows across compute, networking, storage, and software teams with measurable service improvements
  • Experience developing inclusive teams that foster ownership, knowledge transfer, thoughtful decision-making, and career growth

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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