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 build an extraordinary team to optimize datacenter resource usage, drive operational excellence through automation, and create a cost-effective global computing infrastructure. Help us solve strategic challenges and implement methodologies, tools, and metrics for effective resource utilization in a heterogeneous compute environment. 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
What we need to see:
Bachelor’s degree or equivalent experience in Computer Science, Electrical Engineering or related field or similar area.
Minimum 4 years of experience leading AI/ML and software development teams as a people manager with 10+ overall 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 collaborator management 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 people management and team-building skills. Can coach and grow talent, cultivate healthy engineering culture, and attract/retain talent. Ability to build 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
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Top Skills
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.”
