NVIDIA
Senior Deep Learning Framework Communications Engineer
$184K–$356K
US, CA, Santa Clara +4 · Senior · Full-time · Posted Oct 13, 2026
- Location
- US, CA, Santa Clara
US, MA, Westford
US, TX, Austin
US, Remote
US, NC, Durham - Experience
- 8+ software engineering and HPC/AI experience.
- Education
- B.S., M.S. or PhD in Computer Science or a related field, or equivalent experience.
About the job
Integrates and optimizes GPU communication technologies in AI frameworks and workloads, including large-scale training and inference.
What you'll do
- Integrate communication library features into AI frameworks and analyze their performance.
- Characterize multi-GPU AI workloads and improve compiler and communication performance.
- Design fault-tolerant, elastic solutions and author communication or fused compute-communication kernels.
What they ask for
- B.S., M.S. or PhD in Computer Science or a related field, or equivalent experience.
- Experience developing or integrating Deep Learning Frameworks or inference engines such as PyTorch, JAX, TRT-LLM, vLLM or SGLang.
- Prototyping and development with Python, C++, CUDA or related DSLs; understanding of AI models, parallelism or compiler technologies.
- Experience benchmarking AI clusters and familiarity with at least one performance profiler toolchain.
Nice to have
- Parallel programming experience with a communication runtime such as NCCL, NVSHMEM or MPI.
- Expertise in training, distributed inference, MoE, reinforcement learning, kernel authoring or AI compiler pattern matching and lowering.
Pay
184,000 USD - 287,500 USD (base salary, Level 4); 224,000 USD - 356,500 USD (base salary, Level 5)
Tools
PyTorch, TRT-LLM, vLLM, SGLang, JAX, Python, C++, CUDA
AI focus
Integrates GPU communication technologies into AI frameworks; analyzes AI workloads and develops compiler, kernel, and distributed workload improvements for training and inference.
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