5 days ago
Tel Aviv-Yafo, IsraelSenior
Responsibilities
- Enhance NVIDIA GPU networking offerings, including NVIDIA Dynamo, NIXL, and UCX, for AI workloads.
- Co-design hardware features in GPUs, DPUs, and interconnects to accelerate data movement, inference, and model serving.
- Evaluate technologies, innovations, and partner relationships against the technology roadmap and business value.
- Lead architecture and design of runtime systems, communication libraries, and AI-specific technologies.
- Lead proof-of-concept development to evaluate and advance new technologies.
- Drive architectural and development efforts across distributed AI, deep learning, data analytics, HPC, SDN, virtualization, and storage.
Requirements
- M.Sc. or Ph.D. in Computer Science, Electrical Engineering, or Computer Engineering, or equivalent experience.
- At least 5 years of industry experience in system architecture, AI systems architecture, AI scaling, AI framework parallelism, or deep learning training workloads.
- Experience with algorithm design, system programming, computer architecture, operating systems, virtualization, networking, and storage.
- Deep understanding of performance profiling, optimization techniques, and defining and using hardware features.
- Strong programming and software development skills.
- Ability to work and communicate effectively in a multinational, multi-time-zone corporate environment.
- Preferred qualifications include a research track record and experience with CPU, GPU, memory, storage, and networking system architecture.
- Knowledge of deep learning frameworks and AI communication libraries such as NCCL, UCX, and MPI.
- Understanding of inference and training workloads and optimizations, including Prefill/Decode, data parallelism, tensor parallelism, and FDSP.
Benefits
- NVIDIA describes a diverse, equal-opportunity work environment.
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.