Nvidia Software Engineering Intern GPU Communications Networking – Fall 

United States, California 

825054931

• Learn about GPU communication runtimes for Deep Learning frameworks (e.g. NCCL for TensorFlow/Pytorch) and HPC programming interfaces (e.g. NVSHMEM, UCX for MPI/OpenSHMEM) on GPU clusters.
• In-depth performance characterization of one of these runtimes to identify new features
• Enhance the existing CI/CD infrastructure
• Design, implement and maintain system software that enables interactions among GPUs and interactions between GPUs and other system components.
• Create proof-of-concepts to evaluate and motivate extensions in programming models, new designs in runtimes and new features in hardware.

• Pursuing M.S./Ph.D. degree in CS/CE.
• Excellent C/C++ programming and debugging skills.
• Strong experience with Linux.
• Expert understanding of computer system architecture and operating systems.
• Experience with parallel programming interfaces and communication runtimes.
• Ability and flexibility to work and communicate effectively in a multi-national, multi-time-zone corporate environment.

• Deep understanding of technology and passionate about what you do.
• Experience with CUDA programming and NVIDIA GPUs.
• Knowledge of high-performance networks like InfiniBand, iWARP etc.
• Experience with HPC applications.
• Experience with Deep Learning Frameworks such PyTorch, TensorFlow, etc.
• Strong collaborative and interpersonal skills, specifically a proven ability to effectively guide and influence within a dynamic matrix environment.

You will also be eligible for Intern