Senior HPC and AI Network Software Architect

NVIDIA is a technology company with over 25 years of experience in computer graphics, PC gaming, and accelerated computing. The company focuses on AI to define the next era of computing, involving GPUs as central components in computers, robots, and self-driving cars. The role is part of a team building software and hardware for AI at a large scale.

• Ph.D. or equivalent industry experience in computer science, computer engineering, or a related field.
• 5+ years of experience in systems programming, parallel or distributed computing, high-performance networking, or large-scale data movement.
• Strong programming skills in C++, Python, and ideally CUDA or other GPU programming models.
• Extensive hands-on experience with AI frameworks such as PyTorch, TensorFlow, and JAX.
• Demonstrated success in developing high-throughput, low-latency systems with understanding of software stacks, hardware capabilities, and system bottlenecks.
• Strong collaboration skills in a multi-national, interdisciplinary environment.

• Build and evolve the architecture of scalable software systems for distributed AI training and inference, focusing on throughput, latency, resiliency, and memory efficiency across cluster-scale deployments.
• Develop and evaluate next-generation communication and runtime capabilities in libraries such as NCCL, UCX, and UCC.
• Partner with AI framework teams (TensorFlow, PyTorch, JAX) and internal platform teams to build integrations and improve performance and reliability.
• Collaborate on hardware and system-level features across GPUs, DPUs, and interconnects to enhance data movement and capabilities for training, inference, and model serving at scale.
• Drive innovation across runtime systems, communication libraries, and AI-specific protocol layers, turning new ideas into practical capabilities and implementations.