Nvidia Senior SRE Engineering Leader – AI Research Clusters 

United States, Texas 

570418621

As SRE Leader, you will build and operate large scale GPU clusters across various cloud providers. You will help design and implement processes, tools and systems that transform this massive operational experience into an overall improvement to the ecosystem. From improving the design of our next gen GPUs, improving our tooling and SW stack, how we build and operate large scale GPU clusters, and the best practices the Industry should follow to get the best value out of our Accelerated Computing Vision.

What you'll be doing:

• Manage distributed, multi-location GPU clusters for AI research.

• Lead a team of SREs, driving cluster operational excellence and efficiency.

• Deliver scalable distributed systems and AI services in fast-paced environments.

• Build strong, globally distributed teams and drive technical strategy.

• Collaborate across the company to improve the GPU ecosystem for AI use cases.

• Solve reliability, efficiency, and productivity challenges for GPU infrastructure.

• Define strategy, manage projects, and drive technical leadership across multiple areas.

• Collaborate with internal collaborators to ensure transparency on budget and operational efficiency.

What we need to see:

• 10+ overall years in engineering management; 3+ in leadership roles.

• Bachelor’s or Master’s in Computer Science or a related field, or equivalent experience.

• Experience supporting AI/ML workloads and driving operational standard methodologies.

• Strong Unix/Linux knowledge and proficiency in at least two programming languages (Perl, Python, Go).

• Expertise in managing large-scale distributed systems and AI/HPC environments.

• Leadership experience, mentoring, and coaching skills.

• Ability to quickly learn and integrate new technologies.

• Strong collaboration skills across engineering, server, storage, and security teams.

Ways to stand out from the crowd:

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

• Familiarity with InfiniBand, RDMA, Slurm, LustreFS, BCM.

• Familiarity with deep learning frameworks like PyTorch and TensorFlow