Senior HPC & AI Network Architect for Scalable AI Infra

NVIDIA; Zürich; Vor Ort; CHF 180.000 - 240.000; Vollzeit

Zusammenfassung

NVIDIA in Zürich, Switzerland, seeks a Senior HPC and AI Network Software Architect to shape the next generation of scalable AI infrastructure. This role focuses on distributed training, real-time inference, and efficient communication across large GPU clusters.

You will collaborate with AI framework teams and internal platforms to deliver end-to-end performance, integrate NCCL/UCX/UCC, and drive hardware-software co-design across GPUs, DPUs, and interconnects for training, inference, and model

Qualifikationen

• PhD or equivalent in CS/CE or closely related field.
• 5+ years in systems programming, distributed computing, or large-scale data movement.
• Strong programming in C++, Python; CUDA or GPU models ideal.
• Extensive hands-on experience with AI frameworks (PyTorch, TensorFlow, JAX).
• Experience building production-quality, high-throughput, low-latency software.
• Ability to reason across software stacks, hardware, and bottlenecks.

Aufgaben

• Build and evolve scalable software architectures for distributed AI training and inference with focus on throughput and latency.
• Develop and evaluate next-generation communication/runtime capabilities in NCCL, UCX, and UCC.
• Partner with AI framework teams and platform teams to build integrations and improve performance.
• Collaborate on hardware and system-level features across GPUs, DPUs, and interconnects.
• Drive innovation across runtime systems and protocol layers to turn ideas into robust implementations.

Kenntnisse

PhD/Equivalent

Systems programming

C++

Python

CUDA/GPU programming

AI frameworks (PyTorch, TensorFlow, J&

Ausbildung

PhD or equivalent

Tools

NCCL

UCX

UCC

Jobbeschreibung

NVIDIA in Zürich, Switzerland, seeks a Senior HPC and AI Network Software Architect to shape the next generation of scalable AI infrastructure. This role focuses on distributed training, real-time inference, and efficient communication across large GPU clusters.

You will collaborate with AI framework teams and internal platforms to deliver end-to-end performance, integrate NCCL/UCX/UCC, and drive hardware-software co-design across GPUs, DPUs, and interconnects for training, inference, and model