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NVIDIA

Senior DGX Cloud AI Infrastructure Software Engineer

NVIDIA is hiring a Senior DGX Cloud AI Infrastructure Software Engineer in Shanghai, China. Level rates it ; you can apply on NVIDIA.

Level's read on this job

  • Level rates this software engineer role Builds AI ●●●●: the job is building AI systems.
  • Tools and skills the posting cites include PyTorch, TensorFlow and JAX.
  • Level classifies it as a senior role.
  • Level lists 2,700+ other open roles at NVIDIA.

AI in this role

pytorchtensorflowjax
ai-research

Joining NVIDIA's DGX Cloud Team means contributing to the infrastructure that powers our innovative AI research. This team focuses on optimizing efficiency and resiliency of AI workloads, as well as developing scalable AI and Data infrastructure tools and services. Our objective is to deliver a stable, scalable environment for AI researchers, providing them with the necessary resources and scale to foster innovation. We are seeking an AI infrastructure software engineer to join our team. You'll be instrumental in designing, building, and maintaining AI infrastructure that enable large-scale AI training and inferencing. The responsibilities include implementing software and systems engineering practices to ensure high efficiency and availability of AI systems.

As a senior DGX Cloud AI Infrastructure software engineer at NVIDIA, you will have the opportunity to work on innovative technologies that power the future of AI and data science, and be part of a dynamic and supportive team that values learning and growth. The role provides the autonomy to work on meaningful projects with the support and mentorship needed to succeed, and contributes to a culture of blameless postmortems, iterative improvement, and risk-taking. If you are seeking an exciting and rewarding career that makes a difference, we invite you to apply now!

What you’ll be doing:

  • Develop infrastructure software and tools for large-scale AI, LLM, and GenAI infrastructure.

  • Develop and optimize tools to improve infrastructure efficiency and resiliency.

  • Root cause and analyze and triage failures from the application level to the hardware level

  • Enhance infrastructure and products underpinning NVIDIA's AI platforms.

  • Co-design and implement APIs for integration with NVIDIA's resiliency stacks.

  • Define meaningful and actionable reliability metrics to track and improve system and service reliability.

  • Skilled in problem-solving, root cause analysis, and optimization.

What we need to see:

  • Minimum of 8+ years of experience in developing software infrastructure for large scale AI systems.

  • Bachelor's degree or higher in Computer Science or a related technical field (or equivalent experience).

  • Strong debugging skills and experience in analyzing and triaging AI applications from the application level to the hardware level.

  • Proven track record in building and scaling large-scale distributed systems.

  • Experience with AI training and inferencing and data infrastructure services.

  • Familiar in operating large-scale observability platforms for monitoring and logging (e.g., ELK, Prometheus, Loki).

  • Proficiency in programming languages such as Python, C/C++, script languages

  • Excellent communication and collaboration skills, and a culture of diversity, intellectual curiosity, problem solving, and openness are essential.

Ways to stand out from the crowd:

  • Experience in working with the large scale AI cluster

  • Strong understanding of NVIDIA GPUs, network technologies (RDMA, IB, NCCL)

  • Good understanding on DL frameworks internal PyTorch, TensorFlow, JAX, and Ray

  • Experience and root cause analysis of failures and datacenter scale

  • Strong background in software design and development.

NVIDIA leads the way in groundbreaking developments in Artificial Intelligence, High-Performance Computing, and Visualization. The GPU, our invention, serves as the visual cortex of modern computers and is at the heart of our products and services. Our work opens up new universes to explore, enables amazing creativity and discovery, and powers what were once science fiction inventions, from artificial intelligence to autonomous cars. NVIDIA is looking for exceptional people like you to help us accelerate the next wave of artificial intelligence.

How we rate this

Senior DGX Cloud AI Infrastructure Software Engineer at NVIDIA rates 87 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.

Classification

Builds AI. The job is building AI systems.

  1. ●●●● Builds AI80 to 100
  2. ●●●○ Works on AI60 to 79
  3. ●●○○ Uses AI40 to 59
  4. ●○○○ 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

AI ResearchPyTorchTensorFlowJAX

Also common in software engineer jobs at this level

Pay

Typical software engineer job
$168k

This posting doesn't list pay. Use the typical software engineer figure when pay comes up. See software engineer jobs

Questions you could be asked

  1. Tell me about a research question you investigated. What did you find?
  2. Walk me through how you've used PyTorch in your day-to-day work.
  3. What are the limits of TensorFlow that you've run into, and how did you work around them?
  4. What's a project where you used JAX hands-on?
  5. How would you decide a model or AI system is ready to ship?

Adapt your resume

  • List these exact terms on your resume: AI Research, PyTorch, TensorFlow, and JAX. 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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