NVIDIA Switzerland AG
Principal Software Architect, GPU Networking Research(m/w/x)
Full-timeOn-siteSenior
Zürich
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NVNVIDIA
Senior GPU Networking Architect(m/w/x)
Zürich
Full-timeOn-siteSenior
AI/ML
Nejo AI Summary
Optimizing GPU communication kernels for AI acceleration. 5+ years CUDA programming and GPU architecture knowledge required. Hybrid work, 4-day work week.
Requirements
- 5+ years CUDA programming, including writing and optimizing GPU kernels
- M.Sc. or equivalent in computer science, computer engineering, or related field
- Strong understanding of GPU architecture fundamentals
- Experience with systems-level C/C++ development in performance-critical environments
- Familiarity with GPU data movement mechanisms
- Ability to read and reason about GPU performance profiles
- Strong collaboration skills in multi-national, interdisciplinary environment
- Experience developing or optimizing communication kernels in NCCL, NVSHMEM, or similar
- Understanding of distributed deep learning parallelism techniques
- Background in RDMA, InfiniBand, high-speed networking, and GPU system topology
- Experience with overlap techniques to hide communication latency
- Proven experience evaluating and optimizing large-scale LLM training or inference workloads
Tasks
- Build and optimize GPU communication kernels
- Implement GPU communication kernels
- Optimize GPU communication kernels
- Improve kernel efficiency using GPU architecture knowledge
- Minimize latency in GPU kernels
- Overlap computation with communication
- Develop GPU-resident communication primitives
- Develop device-side APIs
- Profile GPU kernels end-to-end
- Tune GPU kernels end-to-end
- Identify compute, memory, and network bottlenecks
- Drive targeted GPU kernel optimizations
- Co-design communication strategies with teams
- Build proofs-of-concept for communication strategies
- Conduct experiments for communication strategies
- Perform quantitative modeling for communication strategies
- Contribute to evolving programming models
- Expose GPU-aware networking capabilities
Work Experience
- 5 years
Education
- Master's degree
Languages
- English – Business Fluent
Tools & Technologies
- CUDA
- C/C++
- GPUDirect RDMA
- Nsight Compute
- Nsight Systems
- NCCL
- NVSHMEM
- RDMA
- InfiniBand
- NVLink
- NVSwitch
- PCIe
- PyTorch
- TensorRT-LLM
- vLLM
Find the original job posting in its most current version here. Nejo automatically captured this job from the website of NVIDIA and processed the information on Nejo with the help of AI for you. Despite careful analysis, some information may be incomplete or inaccurate. Please always verify all details in the original posting! Content and copyrights of the original posting belong to the advertising company.
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NVNVIDIA
Senior GPU Networking Architect(m/w/x)
Zürich
Full-timeOn-siteSenior
AI/ML
Nejo AI Summary
Optimizing GPU communication kernels for AI acceleration. 5+ years CUDA programming and GPU architecture knowledge required. Hybrid work, 4-day work week.
Requirements
- 5+ years CUDA programming, including writing and optimizing GPU kernels
- M.Sc. or equivalent in computer science, computer engineering, or related field
- Strong understanding of GPU architecture fundamentals
- Experience with systems-level C/C++ development in performance-critical environments
- Familiarity with GPU data movement mechanisms
- Ability to read and reason about GPU performance profiles
- Strong collaboration skills in multi-national, interdisciplinary environment
- Experience developing or optimizing communication kernels in NCCL, NVSHMEM, or similar
- Understanding of distributed deep learning parallelism techniques
- Background in RDMA, InfiniBand, high-speed networking, and GPU system topology
- Experience with overlap techniques to hide communication latency
- Proven experience evaluating and optimizing large-scale LLM training or inference workloads
Tasks
- Build and optimize GPU communication kernels
- Implement GPU communication kernels
- Optimize GPU communication kernels
- Improve kernel efficiency using GPU architecture knowledge
- Minimize latency in GPU kernels
- Overlap computation with communication
- Develop GPU-resident communication primitives
- Develop device-side APIs
- Profile GPU kernels end-to-end
- Tune GPU kernels end-to-end
- Identify compute, memory, and network bottlenecks
- Drive targeted GPU kernel optimizations
- Co-design communication strategies with teams
- Build proofs-of-concept for communication strategies
- Conduct experiments for communication strategies
- Perform quantitative modeling for communication strategies
- Contribute to evolving programming models
- Expose GPU-aware networking capabilities
Work Experience
- 5 years
Education
- Master's degree
Languages
- English – Business Fluent
Tools & Technologies
- CUDA
- C/C++
- GPUDirect RDMA
- Nsight Compute
- Nsight Systems
- NCCL
- NVSHMEM
- RDMA
- InfiniBand
- NVLink
- NVSwitch
- PCIe
- PyTorch
- TensorRT-LLM
- vLLM
Find the original job posting in its most current version here. Nejo automatically captured this job from the website of NVIDIA and processed the information on Nejo with the help of AI for you. Despite careful analysis, some information may be incomplete or inaccurate. Please always verify all details in the original posting! Content and copyrights of the original posting belong to the advertising company.
About the Company
NVIDIA
Industry
IT
Description
The company is developing groundbreaking solutions in Virtual Reality, Artificial Intelligence, Deep Learning, and Autonomous Vehicles.
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