Senior System Software Architect, HPC and AI Networking
NVIDIA is hiring a Senior System Software Architect, HPC and AI Networking in Shanghai, China. Level rates it ; you can apply on NVIDIA.
Level's read on this job
- Builds AI ●●●● is how Level rates this role: the job is building AI systems.
- The posting mentions PyTorch, TensorFlow and JAX among its tools and skills.
- Level classes it as a senior role.
- NVIDIA has 2,700+ other open roles on Level.
AI in this role
Design and prototype scalable software systems to optimize distributed AI training and inference workloads.
NVIDIA has been redefining computer graphics, PC gaming, and accelerated computing for more than 25 years. Today, we lead in artificial intelligence, driving advances in natural language processing, computer vision, autonomous systems, and scientific research. We are looking for a forward-thinking HPC and AI Inference Software Architect to help shape the future of scalable AI infrastructure—focusing on distributed training, real-time inference, and communication optimization across large-scale systems.
Join our world-class team of researchers and engineers building next-generation software and hardware systems that power the most demanding AI workloads on the planet.
What you will be doing:
Design and prototype scalable software systems that optimize distributed AI training and inference—focusing on throughput, latency, and memory efficiency.
Develop and evaluate enhancements to communication libraries such as NCCL, UCX, and UCC, tailored to the unique demands of 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 for them.
What we need to see:
Ph.D, Masters, or Bachelors in computer science, computer engineering, electrical engineering or a closely 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, like Prefill/Decode, data parallelism, Tensor parallelism, FDSP, etc...
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 and flexibility to work and communicate effectively in a multi-national, multi-time-zone corporate environment.
Ways to stand out from the crowd:
Deep understanding of technology and passion for what you do.
Strong collaborative and interpersonal skills, specifically a proven ability to effectively guide and influence within a dynamic matrix environment.
Background with designing communication middleware for high-performance computing systems, including RoCE and DPUs.
Background with CUDA programming and NVIDIA GPUs and programming models for emerging architectures.
NVIDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most forward-thinking and hardworking people in the world working for us. If you're creative and autonomous, we want to hear from you!
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.
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How we rate this
Senior System Software Architect, HPC and AI Networking at NVIDIA rates 95 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.
Builds AI. The job is building AI systems.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.
Prepare for this job
Built from this posting and from similar jobs on Level.
Skills and AI tools this role asks for
Questions you could be asked
- Walk me through a computer vision problem you solved, from raw data to a deployed model.
- What NLP problem have you worked on, and how did you measure whether it actually worked?
- Tell me about a project where hpc was part of your work. What did you do?
- Tell me about a project where distributed training was part of your work. What did you do?
- Tell me about a project where deep learning was part of your work. What did you do?
Adapt your resume
- List these exact terms on your resume: Computer vision, NLP, Hpc, Distributed Training, and Deep learning. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
- Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.
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