Senior Deep Learning Framework Communications Engineer

About the role

NVIDIA is seeking a Deep Learning Engineer to integrate new communication libraries into AI frameworks. The ideal candidate will collaborate with teams developing the latest AI models and improve AI compilers to optimize communication performance.

Responsibilities

• Integrate new communication libraries features in AI frameworks from proof of concept to performance analysis to production
• Conduct 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

Requirements

• B.S., M.S., or Ph.D. in Computer Science, or related field (or equivalent experience)
• 5+ years of software engineering and HPC/AI experience
• Development or integration experience with Deep Learning Frameworks such as 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

Qualifications

• 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

Skills

• Python
• C++
• CUDA
• Triton
• cute

Benefits

Base salary range: $152,000 - $241,500 for Level 3, and $184,000 - $287,500 for Level 4. Eligible for equity and benefits.

Pay

Commensurate with experience

Schedule

Varies

Benefits

Varies