Software Engineering Manager - GPU Communications Libraries
NVIDIA is hiring a Software Engineering Manager - GPU Communications Libraries in Santa Clara, United States. It pays $184k-$288k a year and Level rates it ; you can apply on NVIDIA.
Level's read on this job
- Builds AI ●●●● is how Level rates this role: the job is building AI systems.
- Tools and skills the posting cites include PyTorch and TensorFlow.
- Level classifies it as a mid-level role.
- Level lists 2,700+ other open roles at NVIDIA.
AI in this role
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?
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.
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.
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 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!
Your base salary will be determined based on your location, experience, and other objective job-related factors. The expected base salary ranges for this position are:184,000 USD – 287,500 USD for Level 2; and 224,000 USD – 356,500 USD for Level 3.
You will also be eligible for equity and benefits.
Applications for this job will be accepted at least until November 3, 2026.This posting is for an existing vacancy.
NVIDIA uses AI tools in its recruiting processes.
NVIDIA is committed to fostering an inclusive work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.How we rate this
Software Engineering Manager - GPU Communications Libraries at NVIDIA rates 84 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.
Builds AI. The job is building AI systems.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.
Prepare for this job
Built from this posting and from similar jobs on Level.
Skills and AI tools this role asks for
Questions you could be asked
- What's a project where you used PyTorch hands-on?
- Walk me through how you've used TensorFlow in your day-to-day work.
- How would you decide a model or AI system is ready to ship?
- Tell me about a time a model underperformed in production. How did you find out, and what did you change?
Adapt your resume
- List these exact terms on your resume: PyTorch and TensorFlow. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
- Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.
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