Senior System Software Architect, HPC and AI Networking at NVIDIA

Beijing, China

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Not SpecifiedCompensation

Senior (5 to 8 years)Experience Level

Full TimeJob Type

UnknownVisa

AI, HPC, NetworkingIndustries

Requirements

Ph.D., Master’s, or Bachelor’s degree in Computer Science, Computer Engineering, Electrical Engineering, or a related field
5+ years of experience in DNNs, Scaling of DNNs, Parallelism of DNN frameworks, or deep learning training workloads
Deep understanding of Inference and Training workloads and optimizations (e.g., Prefill/Decode, data parallelism, Tensor parallelism, FDSP)
Experience with AI network parallelism using collective libraries and RDMA/RoCE
Background in algorithm design, system programming, and computer architecture
Strong programming and software development skills
Ability to work effectively in a multi-national, multi-time-zone corporate environment

Responsibilities

Design and prototype scalable software systems that optimize distributed AI training and inference
Develop and evaluate enhancements to communication libraries such as NCCL, UCX, and UCC, tailored to deep learning workloads
Collaborate with AI framework teams (e.g., TensorFlow, PyTorch, JAX) to improve integration, performance, and reliability of communication backends
Co-design hardware features (e.g., in GPUs, DPUs, or interconnects) that accelerate data movement and enable new capabilities for inference and model serving
Contribute to the evolution of runtime systems, communication libraries, and AI-specific protocol layers
Collaborate with customers to understand their needs and provide innovative solutions

Skills

Key technologies and capabilities for this role

NCCLUCXUCCTensorFlowPyTorchJAXRDMARoCEDNNData ParallelismTensor ParallelismSystem ProgrammingComputer Architecture

Questions & Answers

Common questions about this position

What is the work arrangement for this position?

The position is hybrid.

What is the salary for this role?

This information is not specified in the job description.

What skills and experience are required for this Senior System Software Architect role?

Candidates need 5+ years of experience in DNNs, scaling of DNNs, parallelism of DNN frameworks, or deep learning training workloads, deep understanding of inference and training workloads, experience with AI network parallelism using collective libraries and RDMA/RoCE, strong programming skills, and ability to work in a multi-national environment.

What is the company culture like at NVIDIA?

NVIDIA is committed to fostering a diverse and inclusive work environment and is an equal opportunity employer.

How do I apply for this position?

Application instructions are not specified; please refer to NVIDIA’s careers website for details.

NVIDIA

Designs GPUs and AI computing solutions

About NVIDIA

NVIDIA designs and manufactures graphics processing units (GPUs) and system on a chip units (SoCs) for various markets, including gaming, professional visualization, data centers, and automotive. Their products include GPUs tailored for gaming and professional use, as well as platforms for artificial intelligence (AI) and high-performance computing (HPC) that cater to developers, data scientists, and IT administrators. NVIDIA generates revenue through the sale of hardware, software solutions, and cloud-based services, such as NVIDIA CloudXR and NGC, which enhance experiences in AI, machine learning, and computer vision. What sets NVIDIA apart from competitors is its strong focus on research and development, allowing it to maintain a leadership position in a competitive market. The company's goal is to drive innovation and provide advanced solutions that meet the needs of a diverse clientele, including gamers, researchers, and enterprises.

Santa Clara, CaliforniaHeadquarters

1993Year Founded

$19.5MTotal Funding

IPOCompany Stage

Automotive & Transportation, Enterprise Software, AI & Machine Learning, GamingIndustries

10,001+Employees

Benefits

Company Equity

401(k) Company Match

Risks

Increased competition from AI startups like xAI could challenge NVIDIA's market position.

Serve Robotics' expansion may divert resources from NVIDIA's core GPU and AI businesses.

Integration of VinBrain may pose challenges and distract from NVIDIA's primary operations.

Differentiation

NVIDIA leads in AI and HPC solutions with cutting-edge GPU technology.

The company excels in diverse markets, including gaming, data centers, and autonomous vehicles.

NVIDIA's cloud services, like CloudXR, offer scalable solutions for AI and machine learning.

Upsides

Acquisition of VinBrain enhances NVIDIA's AI capabilities in the healthcare sector.

Investment in Nebius Group boosts NVIDIA's AI infrastructure and cloud platform offerings.

Serve Robotics' expansion, backed by NVIDIA, highlights growth in autonomous delivery services.

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