Software Engineering Manager - GPU Communications Libraries

We are the GPU Communications Libraries and Networking team at NVIDIA. We deliver communication libraries like NCCL, NVSHMEM, UCX for Deep Learning and HPC. DL and HPC applications have a huge compute demand already and run on scales which go up to tens of thousands of GPUs. The GPUs are connected with high-speed interconnects (eg. NVLink, PCIe) within a node and with high-speed networking (eg. Infiniband, Ethernet) across the nodes.

Communication performance between the GPUs has a direct impact on the end-to-end application performance; and the stakes are even higher at huge scales! We are looking for a technical leader to manage our NVSHMEM and UCX libraries. This is an outstanding opportunity to push the limits on the state-of-the-art and deliver platforms the world has never seen before.

What you will be doing:

• Lead, mentor, and grow your library engineering team and be responsible for the planning and execution of projects as well as the quality, and performance of your libraries.
• Participate in feature design and implementation.
• Interact with internal and external partners and researchers to understand their use cases and requirements.
• Collaborate with engineering teams, program and product management, and partners to define the product roadmap.
• Continuously review and identify improvement opportunities in established processes, infrastructure, and practices.

What we need to see:

• 10+ overall years of experience in the software industry with specialization in HPC networking or system software.
• 4+ years of management experience.
• BS, MS, or Ph.D. in CS, CE, EE (related technical field) or equivalent experience.
• Prior systems software or communication runtime or high performance networking software development experience.
• Strong understanding of computer system architecture, operating systems principles, HW-SW interactions and performance analysis/optimizations.
• Excellent C/C++ programming and debugging skills in Linux.
• Experience balancing multiple projects with competing priorities.
• Flexibility to work and communicate effectively across different teams and timezones.

Ways to stand out:

• Experience with parallel programming models (MPI, SHMEM) and communication runtimes.
• Background with RDMA, high-performance networking technologies, and network architecture.
• Experience with Deep Learning Frameworks such as PyTorch, TensorFlow, etc.

NVIDIA offers a diverse, supportive environment where everyone is inspired to do their best work. Join the team and make a lasting impact on the world.