Principal Deep Learning Communication Architect

What You’ll Be Doing

• Architecture Leadership: Define the long-term technical roadmap for communication libraries across NVIDIA’s next-generation platforms.
• You will ensure the seamless scaling of models to clusters comprising hundreds of thousands of nodes.
• AI Communication Library Design: Lead the development of next-generation communication primitives and collective algorithms.
• This includes optimizing for heterogeneous interconnects such as NVLink, Spectrum-X (Ethernet), and Quantum-X (InfiniBand).
• Application-Communication Library Co-Design: Partner with application developers to architect and implement specialized communication primitives.
• You will ensure that AI and HPC libraries—including NCCL, NIXL, NVSHMEM, UCC, and UCX—evolve to meet the requirements of trillion-parameter and Agentic AI.
• Hardware/Software Co-Design: Collaborate with silicon architects and software engineers to influence hardware specifications for next-generation networking, ensuring they meet the evolving demands of trillion-parameter LLMs and Agentic AI.
• Quantitative Modeling: Develop high-fidelity analytical models and simulators to predict system behavior under emerging workloads.

What We Need To See

• Ph.D. or M.S. in Computer Science, Electrical Engineering, or a related field (or equivalent experience), with 12+ years of industry experience in high-performance computing (HPC) or distributed deep learning.
• Deep understanding of 3D parallelism (Data, Tensor, Pipeline) and advanced strategies including Context Parallelism, Expert Parallelism, and Zero Redundancy Optimizer (ZeRO) variants.
• Deep technical proficiency with NCCL, UCX, UCC, NVSHMEM, or MPI. Experience with RDMA, RoCE, and low-level InfiniBand verbs is required.
• Advanced knowledge of high-throughput inference engines and schedulers, specifically TensorRT-LLM, vLLM, SGLang, and NVIDIA Dynamo.
• Expert knowledge of the NVIDIA GPU memory hierarchy (HBM3e/HBM4, L2 cache) and CUDA programming models.

How To Stand Out

• Hands-on experience developing within Megatron-Core, DeepSpeed, or JAX/XLA, with an understanding of how these frameworks interact with low-level communication runtimes is a plus.
• Significant upstream contributions to major open-source projects (e.g., PyTorch Distributed, KServe, or Ray).
• A proven track record of deploying and optimizing models on NVIDIA platforms or similar rack-scale systems.
• A strong portfolio of patents or papers in top-tier systems/architecture venues (e.g., ISCA, ASPLOS, NeurIPS, SC).

Benefits

Competitive salaries and a generous benefits package. Applications for this job will be accepted at least until April 18, 2026. This posting is for an existing vacancy. NVIDIA uses AI tools in its recruiting processes. NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.