Senior Deep Learning Framework Communications Engineer
About the role
NVIDIA is seeking a motivated Deep Learning Engineer to integrate new communication libraries features in AI frameworks, conduct performance benchmarking on AI clusters, and collaborate with teams working on the latest AI models.
Responsibilities
- Integrate new communication libraries features in AI frameworks: from PoC to performance analysis to production
- 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
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++
- NVIDIA CUDA
- One or more of these areas: Parallel Programming, AI Compiler, Performance Profiling, HPC Communication
Benefits
Base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is $152,000 - $241,500 for Level 3, and $184,000 - $287,500 for Level 4. Eligible for equity and benefits.
Pay
Base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is $152,000 - $241,500 for Level 3, and $184,000 - $287,500 for Level 4.
Schedule
Not specified.
Benefits
Not specified.
Skills
- Python
- C++
- NVIDIA CUDA
- One or more of these areas: Parallel Programming, AI Compiler, Performance Profiling, HPC Communication
Benefits
Not specified.
Pay
Not specified.
Schedule
Not specified.
Benefits
Not specified.