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# Software Engineering Manager - GPU Communications Libraries

- **Company:** NVIDIA Ltd.
- **Location:** Santa Clara, CA, United States
- **Experience:** Experienced
- **Salary:** $184,000.0 - $287,500.0
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, C++ (Programming Language), Nvidia CUDA, Computer Programming, Computer Networks, Computer Graphics, Software Debugging, Linux, Ethernet, Network Topologies, InfiniBand, Network Architecture, OpenMP, Remote Direct Memory Access, Tensorflow, Software Engineering, Systems Architecture, System Software, Graphics Processing Unit (GPU), Computer Network Technologies, Pytorch, Deep Learning, Parallel Computation
- **Published:** October 31, 2026
- **Apply:** https://www.careerbuilder.com/job-details/software-engineering-manager-gpu-communications-libraries-santa-clara-ca--741deeb5-347b-4876-b9db-2440619eccd2

## About the Role

Software Engineering, Engineering Management, GPU (Graphics Processing Unit), Deep Learning, GPU (Graphics Processing Unit), Technical Leadership, Mentoring, Project Planning, Use Cases, Product Management, * 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.

Ways to stand out from the crowd:

 * 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., NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It's a unique legacy of innovation that's fueled by great technology-and amazing people. Today, we're tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what's never been done before takes vision, innovation, and the world's best talent. As an NVIDIAN, you'll be immersed in a diverse, supportive environment where everyone is inspired to do their best work. Come join the team and see how you can make a lasting impact on the world. NVIDIA is widely considered to be one of the technology world's most desirable employers. We have some of the most forward-thinking and hardworking people on the planet working for us. If you're creative and autonomous, we want to hear from you!

## Description

* 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.