Senior Deep Learning Framework Communications Engineer

Nvidia

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Remote

Quick summary

Work type
Remote
Location
Santa Clara, CAWestford, MAAustin, TXDurham, NC
Salary
$184,000–$287,500 / yr
Employment
Full-time
Posted
9 days ago
Freshness
Confirmed live today
Nearby
99+ roles within 25 mi

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $210k
This role $236k
$154k $302k
below market most similar roles pay here above market

This role pays more than 70% of similar roles. Most pay $177,900–$242,062 — the blue band above. At the midpoint, this role pays about $236k versus about $210k for comparable roles.

Based on 240 similar postings.

Employer

About Nvidia

Nvidia is a leading designer of graphics processing units (GPUs) and system-on-chip units, powering gaming, professional visualization, data centers, and artificial intelligence workloads. Industry: Semiconductors & AI Computing

Nvidia currently has 1623 open roles on FindRole.

Listed pay typically runs $184,000–$287,500 across 1110 roles with salary data.

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At a glance

TL;DR · Senior Deep Learning Framework Communications Engineer

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The Senior Deep Learning Framework Communications Engineer joins the team responsible for communication libraries like NCCL and NVSHMEM. This role involves integrating new communication library features into AI frameworks, performing deep analysis of AI workloads to identify multi-GPU communication requirements, and improving AI compilers to hide communications or perform automatic fusion. You will design fault-tolerant solutions for large-scale workloads and author custom communication or fused compute-communication kernels. The position requires proficiency in Python, C++, CUDA, and DSLs like Triton or cuTe. You must have experience with frameworks such as PyTorch, JAX, TRT-LLM, vLLM, and SGLang. The work addresses the technical challenge of optimizing communication performance between GPUs for diverse demands ranging from training on 100K GPUs to microsecond latency inference.

Skills

PyTorch JAX TRT-LLM vLLM SGLang CUDA Triton C++ Python NCCL NVSHMEM GPUDirect MPI NVIDIA Nsight Systems PyTorch Profiler High Performance Computing AI Compilers Kernel Authoring MoE

What you'll do

  • Integrate new communication library features into AI frameworks from proof-of-concept to production.
  • Analyze AI workloads to identify multi-GPU communication requirements and performance opportunities.
  • Improve AI compilers to perform automatic fusion or hide communication overhead.
  • Conduct performance characterization of AI workloads on large-scale multi-GPU clusters.
  • Design fault-tolerant and elastic solutions for large-scale or dynamic AI workloads.
  • Author custom communication or fused compute-communication kernels for NVIDIA platforms.
  • Influence the technical roadmap for communication libraries like NCCL and NVSHMEM.

What we're looking for

  • B.S., M.S., or PhD in Computer Science or a related field, or equivalent experience.
  • Software engineering and HPC/AI experience.
  • Development or integration experience with Deep Learning Frameworks like PyTorch and JAX, and inference engines like TRT-LLM, vLLM, or SGLang.
  • Rapid prototyping and development skills with Python, C++, CUDA, or related DSLs like Triton and cuTe.
  • Solid grasp of AI models, parallelisms, and compiler technologies.
  • Experience conducting performance benchmarking on AI clusters and familiarity with performance profiler toolchains.
  • Understanding of HPC/AI communication concepts including 1-sided vs 2-sided communication, elasticity, resiliency, and topology discovery.
  • Experience with parallel programming on communication runtimes like NCCL, NVSHMEM, or MPI (preferred).

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