Software Engineering Manager - GPU Communications Libraries

Nvidia•Santa Clara, CA

33d

About The Position

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. Are you ready for to contribute to the development of innovative technologies and help realize NVIDIA's vision?

Requirements

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 with a successful track record of taking several complex software features or products through the full product life cycle.
Strong understanding of computer system architecture, operating systems principles (aka systems software fundamentals), 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.

Nice To Haves

Experience with parallel programming models (MPI, SHMEM) and at least one communication runtime (MPI, NCCL, NVSHMEM, OpenSHMEM, UCX, UCC). Experience with programming using CUDA, MPI, OpenMP, OpenACC, pthreads.
Background with RDMA, high-performance networking technologies (InfiniBand, RoCE, Ethernet, EFA), network architecture and network topologies. Knowledge of HPC and ML/DL fundamentals.
Experience with Deep Learning Frameworks such PyTorch, TensorFlow, etc.

Responsibilities

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.
This is a technical leadership role so you will 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 to ensure the teams are executing in the most efficient and transparent manner.