Senior Software Architect, AI Systems and Networking

Nvidia

Confirmed live yesterday High trust

Remote

Quick summary

Work type: Remote
Location: Santa Clara, CAAustin, TX
Salary: $224,000–$356,500 / yr
Posted: 115 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 $200k

This role $290k

$140k most similar roles pay here $380k

This role pays more than 97% of similar roles. Most pay $163,337–$235,750 — the shaded band above. At the midpoint, this role pays about $290k versus about $200k for comparable roles.

Based on 239 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, AI Systems and Networking

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As a Senior Software Architect, AI Systems and Networking within the Networking Systems & Software Architecture group, you will own modules and projects end-to-end by scoping research questions and shipping production code. You will architect and implement high-performance communication and memory management libraries for distributed AI while driving hardware-software co-optimization involving GPU, DPU, NIC, and switch components. Your daily work involves profiling data movement across GPU memory, system DRAM, NVMe, and network fabrics, as well as integrating networking capabilities into serving stacks like vLLM, SGLang, and TensorRT-LLM. You will utilize C, C++, and Rust to develop solutions involving InfiniBand, RoCE, RDMA, NVLink, and GPUDirect. The role addresses critical infrastructure problems in AI data movement, including transformer architectures, KV cache mechanics, model parallelism, and distributed training patterns across complex networking fabrics.

Skills

C C++ Rust RDMA InfiniBand RoCE NVLink GPUDirect vLLM SGLang TensorRT-LLM NVMe-oF Distributed Training Performance Profiling Memory Management High-Performance Networking

What you'll do

Architect and implement high-performance communication and memory management libraries for distributed AI.
Drive hardware-software co-optimization using GPUDirect RDMA, NVLink, and next-generation interconnects.
Profile and optimize data movement across GPU memory, system DRAM, NVMe, and network fabrics.
Integrate networking capabilities into production AI serving stacks like vLLM, SGLang, and TensorRT-LLM.
Own projects end-to-end from scoping research questions to shipping production code.
Prototype experimental technologies to evaluate their viability for production use.
Maintain open-source projects and conduct technical design reviews.

What we're looking for

12+ years of experience in systems software and/or networking with demonstrated ownership of complex projects.
MS, PhD, or equivalent experience in Computer Science, Computer Engineering, Electrical Engineering, or a related field.
Solid understanding of high-performance networking including InfiniBand, RoCE, RDMA, NVLink, and GPUDirect.
Proficiency in C/C++/Rust systems programming with expertise in performance profiling and low-level debugging.
Understanding of ML systems concepts such as transformer architectures, KV cache mechanics, model parallelism, and distributed training.
Knowledge of ML inference frameworks like vLLM, SGLang, and TensorRT-LLM.
Knowledge of storage networking including NVMe-oF, GPUDirect Storage, and S3.
Background in Reinforcement Learning systems.

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