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Infrastructure Software Engineer, Deep Learning Libraries Experience: Not Available to Not Available years Location: Shanghai, China Skills: Python, C/C++, Jenkins, GitHub Actions, GitLab, Azure DevOps, AI agents, Git, Perforce, Make, CMake, Bazel, Kubernetes, Docker Company Overview We are now looking for an Infrastructure Software Engineer for Deep Learning Libraries! NVIDIA's Deep Learning Libraries Group is seeking excellent software engineers to enable the next wave of NVIDIAs highest performing deep learning libraries. The role focuses on NVIDIA's open-source products such as CUTLASS. The mission is to design and develop scalable, modular infrastructure that streamlines development, builds, and tests across NVIDIAs diverse set of platforms, and address the needs from the open-source community, with the cutting-edge AI technology. Join our technically diverse team of software engineers and infrastructure experts to design the systems that enable NVIDIA to stay ahead of the competition as we deliver the world's fastest deep learning platforms. What you'll be doing: Designing and developing software for testing and analysis of our codebases Building scalable automation for build, test, integration, and release processes for open-source products Developing and deploying AI agents and similar technology to automate the end-to-end software development cycle Configuring, maintaining, and building upon deployments of industry-standard tools (e.g. Kubernetes, Jenkins, Docker, CMake, Gitlab, Jira, etc.) Advancing the state of the art in those industry-standard tools What we need to see: A Masters Degree in Computer Science or Computer Engineering or equivalent experience. 3+ years of relevant experience Strong programming skills in Python (or similar) and familiarity with C/C++ development Experience setting up, maintaining, and automating continuous integration systems (e.g. Jenkins, GitHub Actions, GitLab pipelines, Azure DevOps) Extensive experience in AI agents technology Fluency in SCM (e.g. Git, Perforce) and build systems (e.g. Make, CMake, Bazel) Ways to stand out from the crowd: Experience designing and developing automation in Jenkins with Groovy (or similar) Background with distributed systems and cluster/cloud computing, especially with Kubernetes Experience designing and developing unit and integration test frameworks Close follow the latest trend in AI industry Track record of identifying useful current technologies and incorporating them into SW development flows This is an opportunity to have a wide impact at NVIDIA by improving development velocity across our many AI/DL/Compute Software projects. Are you creative, driven, and autonomous Do you love a challenge If so, we want to hear from you! .
Here's how to pick the right one and stand out in your application.
144.883Jobs
31.687IN
81%EN
That number is real. WorkMundi's database shows 144,883 open engineer roles across the world. India has the most with 31,687 jobs, followed by the United States with 30,084. If you just finished reading one job ad and felt paralyzed by choice, you're not alone—but this scale is actually an advantage. It means you can afford to be selective.
Start by geography and language. The majority of engineer ads—117,837 of them—have the job posting text written in English. Use that as one filter, but remember: the ad text language tells you nothing about whether the role actually requires you to speak English day-to-day. Read the job description carefully. Then check which countries have the volume you're targeting. Singapore, Poland, and Australia round out the top five after India and the US.
Next, learn who's hiring. Accenture has posted 2,801 engineer roles. andurilindustries, speechify, and jobgether are also actively recruiting. If you're applying to one of these names, research their hiring patterns and interview style before you apply. That homework pays off.
When you interview, expect the question every engineer hears: 'Tell me about a time you had to debug a problem that wasn't in your job description.' Have a specific story ready—not a general one. Name the tools, the deadline pressure, and what you learned. Hiring managers listen for whether you see problem-solving as part of the role itself, not a favour.