Senior AI and HPC Clusters Lead

Posted 3 Days Ago
Be an Early Applicant
Santa Clara, CA
Expert/Leader
Artificial Intelligence • Hardware • Robotics • Software • Metaverse
The Role
Lead the design of GPU compute clusters for AI, HPC, and compute-intensive workloads. Optimize datacenter resource usage and drive operational excellence through automation. Collaborate with multi-functional teams to improve performance and cost-effectiveness of AI computing operations.
Summary Generated by Built In

At NVIDIA, we constantly innovate to amplify human intelligence. Our invention of the GPU sparked revolutions in gaming, computer graphics, and parallel computing. Now, GPU deep learning is driving modern AI forward. Join our GPU AI/HPC Infrastructure team and lead the design of groundbreaking GPU compute clusters for demanding AI, HPC, and compute-intensive workloads. In this role, you'll lead and operate substantial AI GPU Clusters at unprecedented scale. You'll lead an extraordinary team to optimize datacenter resource usage, drive operational excellence through automation, and create a cost-effective global computing infrastructure, and create delightful experience for Internal AI Researchers to improve their developer productivity. Help us solve strategic challenges and implement methodologies, tools, and metrics for effective AI researcher productivity by offering a state of the are GPU computing infrastructure. Make the choice to join NVIDIA today and shape the future of AI computing!

What you'll be doing:

  • Building and improving our ecosystem around GPU-accelerated computing including developing large scale automation solutions.

  • Supporting our researchers to run their flows on our clusters including performance analysis and optimizations of deep learning workflows. Improving reliability and overall Researcher Productivity.

  • Architect and implement brand new strategies to optimize the utilization of our AI computing clusters, driving operational efficiency and resource maximization.

  • Pioneer innovative solutions to streamline support processes, enabling our team to manage an unprecedented scale of GPU resources (10,000+ GPUs per support personnel).

  • Lead the charge in building a future-proof AI computing infrastructure, ensuring seamless scalability and resilience to power groundbreaking AI models and applications.

  • Collaborate with multi-functional teams to identify bottlenecks and opportunities for optimization, continuously improving the performance and cost-effectiveness of our AI computing operations.

  • Empower your team with the tools, processes, and standard methodologies necessary to thrive in a dynamic, high-intensity environment, fostering a culture of operational excellence and continuous improvement

  • Partner closely with AI Researcher to understand their needs and devise strategies and plans to address their pain points.

What we need to see:

  • Bachelor’s degree or equivalent experience in Computer Science, Electrical Engineering or related field or similar experience.

  • Minimum 6 years of experience leading AI/ML and software development teams with 12+ years of relevant experience.

  • Consistent track record of leading high-performance teams in delivering innovative solutions to complex computational challenges, with a demonstrated ability to drive operational excellence and continuous improvement.

  • Exceptional problem-solving skills, with the ability to analyze complex systems, identify bottlenecks, and implement scalable solutions that can accommodate the ever-increasing demands of AI computing.

  • Shown leadership capabilities, with the ability to inspire and motivate multi-functional teams, fostering a culture of collaboration, innovation, and steadfast pursuit of operational excellence.

  • Strong communication and collaboration skills, enabling you to effectively articulate technical concepts to diverse audiences and align priorities across the organization.

  • A passion for pushing the boundaries of what's possible in AI computing, with an aim to continuously explore and implement emerging technologies and standard processes to maintain our competitive edge.

  • Strong team leadership and team-building skills. Can coach and grow talent, cultivate healthy engineering culture, and attract/retain talent. Ability to lead a diverse, broad, and impactful team.

Ways to stand out from the crowd:

  • Experience with Machine Learning and Deep Learning concepts, algorithms and models

  • Familiarity with InfiniBand with IBOP and RDMA

  • Understanding of fast, distributed storage systems like Lustre and GPFS for AI/HPC workloads

  • Familiarity with deep learning frameworks like PyTorch and TensorFlow

NVIDIA offers highly competitive salaries and a comprehensive benefits package. We have some of the most experienced and versatile people in the world working for us and, due to unprecedented growth, our extraordinary engineering teams are growing fast. If you're a creative and autonomous engineer with real passion for technology, we want to hear from you.

The base salary range is 220,000 USD - 339,250 USD. Your base salary will be determined based on your location, experience, and the pay of employees in similar positions.

You will also be eligible for equity and benefits. NVIDIA accepts applications on an ongoing basis.

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.

Top Skills

Cuda
Python
The Company
HQ: Santa Clara, CA
21,960 Employees
On-site Workplace
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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