2 months ago
Zürich, SwitzerlandSenior
Responsibilities
- Architect and evolve scalable software systems for distributed AI training and inference across cluster-scale deployments.
- Develop and evaluate communication and runtime capabilities in NCCL, UCX, and UCC.
- Integrate AI frameworks including TensorFlow, PyTorch, and JAX with communication and runtime systems.
- Collaborate on GPU, DPU, and interconnect hardware-software features to improve data movement, training, inference, and model serving.
- Drive innovation in runtime systems, communication libraries, and AI-specific protocol layers.
Requirements
- Ph.D. or equivalent industry experience in computer science, computer engineering, or a closely related field.
- At least 5 years of experience in systems programming, parallel or distributed computing, high-performance networking, or large-scale data movement.
- Strong C++ and Python programming skills, ideally including CUDA or other GPU programming models.
- Extensive hands-on experience with AI frameworks such as PyTorch, TensorFlow, and JAX.
- Experience building high-throughput, low-latency, performance-critical systems and reasoning across software, hardware, and system bottlenecks.
- Strong collaboration skills in multinational and interdisciplinary environments.
- Preferred expertise with NCCL, UCX, UCC, networking protocols, RDMA, collective communications, congestion-aware transport, or accelerator-aware networking.
- Preferred experience with large-model training and inference serving, hardware-software co-design, GPUs, DPUs, interconnects, sharding, pipelining, expert parallelism, or hybrid parallelism.
Benefits
- NVIDIA offers competitive salaries and a comprehensive benefits package for employees and their families.
Categories
About Nvidia
Nvidia designs and sells GPUs and accelerated computing platforms for data centers, AI/ML, graphics, gaming, and automotive, monetizing through hardware, software platforms (CUDA, AI frameworks), and systems like DGX and networking. Customers include cloud providers, enterprises, researchers, and OEMs. Founded in 1993 and headquartered in Santa Clara, it is a public company traded on NASDAQ under NVDA.