Principal Developer, AI Networking

Nvidia

Confirmed live yesterday High trust

Remote

Quick summary

Work type: Remote
Location: Santa Clara, CATXCOWA
Salary: $272,000–$431,250 / yr
Employment: Full-time
Posted: 137 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 $220k

This role $352k

$132k $463k

below market most similar roles pay here above market

This role pays more than 97% of similar roles. Most pay $177,900–$262,150 — the blue band above. At the midpoint, this role pays about $352k versus about $220k 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 1623 open roles on FindRole.

Listed pay typically runs $184,000–$287,500 across 1110 roles with salary data.

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At a glance

TL;DR · Principal Developer, AI Networking

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JOB TITLE: Principal Developer, AI Networking The AI Networking Codesign and Benchmarking R&D group seeks a senior software engineer to profile, analyze, and optimize AI workloads on large-scale GPU and CPU clusters for distributed Deep Learning LLM training and inference. You will characterize deep learning models, identify performance bottlenecks, and develop performance analysis tools to clarify expectations for new technologies. Your work involves high-performance networking, specifically focusing on collective communication and networking across hardware components like HCAs, Switches, CPUs, and GPUs. You will utilize Python, Bash, and C++ alongside frameworks such as PyTorch and TensorFlow. Key technical requirements include expertise in RDMA, MPI, NCCL, SHARP, and RoCE protocols, as well as experience with CUDA libraries and container-based development environments to co-design network systems for large-scale LLM workloads.

Skills

Python C++ PyTorch CUDA NCCL RDMA MPI RoCE Deep Learning Distributed Systems Bash TensorFlow High-Performance Networking Benchmarking Profiling HCA SHARP

What you'll do

Profile, analyze, and optimize AI workloads on large-scale GPU and CPU clusters for distributed LLM training and inference.
Characterize deep learning models and AI workloads specifically for NVIDIA supercomputers.
Benchmark and analyze high-performance networking performance to identify and resolve system bottlenecks.
Develop a PyTorch trace-based profiling, analysis, and replaying toolset for benchmarking and debugging.
Co-design network systems for LLM workloads by analyzing hardware components like HCAs, switches, CPUs, and GPUs.
Define performance test plans and set performance expectations for new technologies and solutions.
Provide performance analysis insights across hardware and software layers to achieve specific performance targets.

What we're looking for

B.Sc in Computer Science or Software Engineering or equivalent experience.
15+ years of experience with high-performance networking including RDMA, MPI, NCCL, and SHARP.
Demonstrated ability in performance evaluation techniques and approaches.
Experience with NVIDIA GPUs and the CUDA library.
Knowledge of deep learning frameworks like TensorFlow or PyTorch.
Expertise in networking collective communication libraries such as NCCL and protocols like RoCE and RDMA.
Proficiency in programming languages including Python, Bash, and C++.
Experience with a container-based development environment.

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