Senior Software Architect, Deep Learning and HPC Communications

Nvidia

Confirmed live yesterday High trust

Remote

Quick summary

Work type: Remote
Location: Santa Clara, CAWestford, MAAustin, TXDurham, NC
Salary: $224,000–$356,500 / yr
Posted: 6 days ago
Freshness: Confirmed live yesterday
Nearby: 99+ roles within 25 mi

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $213k

This role $290k

$163k most similar roles pay here $377k

This role pays more than 93% of similar roles. Most pay $190,212–$235,750 — the shaded band above. At the midpoint, this role pays about $290k versus about $213k for comparable roles.

Based on 240 similar postings.

Employer

About Nvidia

Nvidia is a leading designer of graphics processing units (GPUs) and system-on-chip units, powering gaming, professional visualization, data centers, and artificial intelligence workloads. Industry: Semiconductors & AI Computing

Nvidia currently has 896 open roles on FindRole.

Listed pay typically runs $184,000–$287,500 across 876 roles with salary data.

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At a glance

TL;DR · Senior Software Architect, Deep Learning and HPC Communications

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As a Senior Software Architect - Deep Learning and HPC Communications within the GPU Communications Libraries and Networking team, you will co-design next-generation data center platforms and scalable communications software. You will investigate performance bottlenecks, design new communication technologies to accelerate AI and HPC workloads, and conduct experiments using quantitative modeling and simulation to evaluate large GPU clusters. The role involves solving critical scaling challenges for systems utilizing tens of thousands of GPUs connected via NVLink, PCIe, InfiniBand, and Ethernet. To succeed, you must possess expert C/C++ programming skills, a deep understanding of operating systems and network architecture, and experience with parallel programming models like MPI or SHMEM and runtimes such as NCCL, NVSHMEM, or UCX. Relevant expertise includes Linux, CUDA, and deep learning frameworks like PyTorch or TensorFlow to optimize communication subsystems.

Skills

C++ C CUDA MPI NCCL NVSHMEM UCX OpenSHMEM InfiniBand NVLink PCIe RoCE PyTorch TensorFlow Linux HPC Deep Learning Network Architecture

What you'll do

Identify and resolve performance bottlenecks in current communication systems.
Design and implement new communication technologies to accelerate AI and HPC workloads.
Co-design next-generation data center platforms with GPU, Networking, and Software architects.
Build proofs-of-concept and conduct experiments to evaluate and drive technical innovations.
Perform quantitative modeling to assess the performance of large-scale GPU clusters.
Use simulation tools to explore the scalability of thousands of GPUs in a network.

What we're looking for

M.S./Ph.D. degree in Computer Science, Computer Engineering, or equivalent experience.
12+ years of relevant experience.
Excellent C/C++ programming and debugging skills.
Experience with parallel programming models such as MPI and SHMEM.
Experience with at least one communication runtime including MPI, NCCL, NVSHMEM, OpenSHMEM, UCX, or UCC.
Deep understanding of operating systems, computer architecture, and system architecture.
Solid knowledge of network architecture, topology, algorithms, and communication scaling for AI and HPC workloads.
Strong experience with Linux.

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