Senior GPU Networking Architect
Salary not listed • Switzerland, Zurich • Full-time
Posted 11d ago
Remote Work Policy
On-site
Employment Type
Full-time
Categories
AI Infrastructure Engineer
About the job
NVIDIA is seeking a Senior GPU Networking Architect to join their networking software group. This role is crucial for building and improving GPU communication kernels, bridging GPU computing with networking by ensuring communication primitives are developed in sync with GPU hardware capabilities. The successful candidate will contribute to the software foundation for the world's largest AI systems, working in a diverse and supportive environment that fosters innovation and impact.
Responsibilities
- Build, implement, and optimize GPU communication kernels for collective and point-to-point operations in large-scale AI systems.
- Enhance kernel efficiency, minimize latency, and overlap computation with communication by leveraging deep knowledge of GPU architecture.
- Develop GPU-resident communication primitives and device-side APIs for fine-grained, kernel-initiated data movement across nodes and accelerators.
- Profile and tune GPU kernels end-to-end, identifying and optimizing bottlenecks at the intersection of compute, memory, and network.
- Collaborate with network software, hardware, and AI framework teams to co-design communication strategies aligned with GPU execution patterns.
- Build proofs-of-concept, conduct experiments, and perform quantitative modeling to evaluate new communication strategies.
- Contribute to the evolution of programming models that expose GPU-aware networking capabilities to application developers.
Requirements
- 5+ years of hands-on CUDA programming, including writing and optimizing non-trivial GPU kernels.
- M.Sc. or equivalent experience in computer science, computer engineering, or a related field.
- Strong understanding of GPU architecture fundamentals (warp scheduling, shared memory, L2 cache, memory coalescing, occupancy tuning, asynchronous execution).
- Experience with systems-level C/C++ development in performance-critical environments.
- Familiarity with GPU data movement mechanisms like GPUDirect RDMA and GPU-initiated communication.
- Ability to read and interpret GPU performance profiles (e.g., Nsight Compute, Nsight Systems) and translate observations into optimizations.
- Strong collaboration skills in a multi-national, interdisciplinary environment.
Benefits
- Highly competitive salaries
- Comprehensive benefits package