Nvidia Senior Software Architect AI HPC 

United States, Texas 

26742358

What you will be doing:

The software architecture group at NVIDIA has openings for software architects in the field of AI and high-performance networking and system software. We research, develop, and deploy solutions in networking hardware, programming environments, and system software to make current and future high-end computer systems more performant, scalable, and usable.

• Creating proofs-of-concept to evaluate and motivate extensions in AI Frameworks (PyTorch/NEMO), HPC programming models (MPI, OpenSHMEM, PGAS), new runtime designs, and new network hardware features.

• Research, design and implement features for AI and HPC communication middleware (NCCL, Open MPI, UCX, UCC, NVSHMEM), and Deep Learning frameworks such as TensorFlow/Pytorch.

• Review, design, and implement features to enhance compiler features to support the NVIDIA networking ecosystem.

• Research, design and develop hardware features relevant to scientific, Deep learning, and data-intensive workloads.

What we need to see:

• A Ph.D. or Master, in computer science, computer engineering, or a closely related field or equivalent experience.

• 5+ years of experience in parallel programming models, and/or network architecture.

• Background in algorithm design, system programming, and computer architecture

• Strong programming and software development skills

• Ability and flexibility to work and communicate effectively in a multi-national, multi-time-zone corporate environment

• Deep understanding of technology and passion for what you do

• Strong collaborative and interpersonal skills, specifically a proven ability to effectively guide and influence within a dynamic matrix environment

Ways to stand out from the crowd:

• Background with designing communication middleware for high-performance computing systems, including InfiniBand, DPUs, Ethernet, and Shared Memory;

• Experience developing and implementing features for compilers, optimizations for compilers, particularly Clang/LLVM, and NVIDIA compilers;

• Experience implementing communications libraries, particularly MPI, OpenSHMEM, NCCL, NVSHMEM, UCX, UCC, or PGAS;

• Background with CUDA programming and NVIDIA GPUs

• Programming models for emerging architectures including hierarchical heterogeneous memory systems and accelerators.