Perform deep analysis of AI workloads and frameworks to identify multi-GPU communication requirements and opportunities. Collaborate hands-on with teams working on the latest AI models.
Improve AI compilers to hide communications or perform automatic fusion.
Conduct in-depth AI workload performance characterization on multi-GPU clusters.
Design fault-tolerant and elastic solutions for large-scale or dynamic AI workloads.
Author custom communication or fused compute-communication kernels to showcase ultimate performance on NV platforms.
Influence the roadmap of communication libraries - NCCL & NVSHMEM.
Collaborate with a very dynamic team across multiple time zones.
What we need to see
B.S, M.S. or PHD in Computer Science, or related field (or equivalent experience) with software engineering and HPC/AI experience
Development or integration experience with Deep Learning Frameworks such PyTorch, JAX, and Inference Engines such as TRT-LLM, vLLM, SGLang
Rapid prototyping and development with Python, C++, CUDA or related DSLs (Triton, cuTe)
Solid grasp of AI models, parallelisms, and/or compiler technologies (e.g. torch.compile)
Experience conducting performance benchmarking on AI clusters. Familiarity with at least one performance profiler toolchain (PyTorch profiler, NVIDIA Nsight Systems)
Understanding of HPC/AI communication concepts (1-sided v 2-sided communication, elasticity, resiliency, topology discovery, etc)
Adaptability and passion to learn new areas and tools
Flexibility to work and communicate effectively across different teams and timezones
Ways to stand out from the crowd
Experience with parallel programming on at least one communication runtime (NCCL, NVSHMEM, MPI). Good understanding of computer system architecture, HW-SW interactions and operating systems principles (aka systems software fundamentals)
Expertise in one or more of these areas: Training, Distributed inference, MoE, Reinforcement Learning, kernel authoring (on CUDA, Triton, cuTe, etc). Experience with programming for compute & communication overlap in distributed runtimes
Experience with AI compiler pattern matching and lowering. Solid understanding of memory hierarchy, consistency model, and tensor layout
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 in the world 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:
- 124,000 USD – 195,500 USD for Level 2; and 152,000 USD – 241,500 USD for Level 3.
You will also be eligible for equity and benefits.
Applications for this job will be accepted at least until November 18, 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.
