{"id":2726738,"url":"https://alion.io/job/nvidia-infrastructure-software-engineer-deep-learning-libraries","title":"Infrastructure Software Engineer, Deep Learning Libraries","company":{"id":6,"name":"NVIDIA","domain":"nvidia.com","url":"https://alion.io/company/nvidia","size_band":"5000+","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Workday","truth_index":{"grade":"B","score":80,"open_postings":817,"ghost_share":0.023,"stale_share":0.736,"repost_share":0.043,"time_to_fill_p50_days":35,"computed_at":"2026-10-26T05:57:25Z"}},"role":"DevOps","role_family":"DevOps","seniority":"middle","employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Shanghai, China","Beijing, China"],"countries":["CN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":28000,"max_usd":73000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":40},"experience_years_min":3,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AI Agents","optional":false},{"name":"Azure DevOps","optional":false},{"name":"C++","optional":false},{"name":"CI/CD","optional":false},{"name":"CMake","optional":false},{"name":"CUTLASS","optional":false},{"name":"Docker","optional":false},{"name":"Git","optional":false},{"name":"GitHub Actions","optional":false},{"name":"GitLab","optional":false},{"name":"Groovy","optional":false},{"name":"Jenkins","optional":false},{"name":"Jira","optional":false},{"name":"Kubernetes","optional":false},{"name":"Python","optional":false},{"name":"Azure","optional":true}],"status":"live","first_seen_at":"2026-05-28T00:00:00Z","employer_posted_date":"2026-05-28","last_verified_at":"2026-10-24T08:48:21Z","board_verified":false,"closed_at":null,"days_open":151,"trust":{"level":"stale","repost_count":0,"flags":["stale"],"days_open":151},"description":"We are now looking for an Infrastructure Software Engineer for Deep Learning Libraries!\nNVIDIA's Deep Learning Libraries Group is seeking excellent software engineers to enable the next wave of NVIDIA’s 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 NVIDIA’s 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.\nWhat you'll be doing:\nDesigning and developing software for testing and analysis of our codebases\n\nBuilding scalable automation for build, test, integration, and release processes for open-source products\n\nDeveloping and deploying AI agents and similar technology to automate the end-to-end software development cycle\n\nConfiguring, maintaining, and building upon deployments of industry-standard tools (e.g. Kubernetes, Jenkins, Docker, CMake, Gitlab, Jira, etc.)\n\nAdvancing the state of the art in those industry-standard tools\n\nWhat we need to see:\nA Masters Degree in Computer Science or Computer Engineering or equivalent experience.\n\n3+ years of relevant experience\n\nStrong programming skills in Python (or similar) and familiarity with C/C++ development\n\nExperience setting up, maintaining, and automating continuous integration systems (e.g. Jenkins, GitHub Actions, GitLab pipelines, Azure DevOps)\n\nExtensive experience in AI agents technology\n\nFluency in SCM (e.g. Git, Perforce) and build systems (e.g. Make, CMake, Bazel)\n\nWays to stand out from the crowd:\nExperience designing and developing automation in Jenkins with Groovy (or similar)\n\nBackground with distributed systems and cluster/cloud computing, especially with Kubernetes\n\nExperience designing and developing unit and integration test frameworks\n\nClose follow the latest trend in AI industry\n\nTrack record of identifying useful new technologies and incorporating them into SW development flows\n\nThis is an opportunity to have a wide impact at NVIDIA by improving development velocity across our many AI/DL/Compute Software projects. 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