{"id":3467625,"url":"https://alion.io/job/nvidia-senior-software-engineer-dgx-cloud-3","title":"Senior Software Engineer - DGX Cloud","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":84,"open_postings":772,"ghost_share":0.022,"stale_share":0.583,"repost_share":0.04,"time_to_fill_p50_days":40,"computed_at":"2026-11-03T05:54:40Z"}},"role":"Backend","role_family":"Backend","seniority":"senior","employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Santa Clara, United States","United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":{"min":224000,"max":356500,"currency":"USD","period":"year","gross":null,"usd_annual":356500},"salary_estimate":null,"experience_years_min":12,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Kubernetes","optional":false},{"name":"Linux","optional":false},{"name":"Machine Learning","optional":false},{"name":"Python","optional":false},{"name":"Rust","optional":false},{"name":"SLURM","optional":false}],"status":"live","first_seen_at":"2026-10-27T00:00:00Z","employer_posted_date":"2026-10-27","last_verified_at":"2026-11-03T15:00:26Z","board_verified":true,"closed_at":null,"days_open":7,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":7},"description":"Join a team of engineers at NVIDIA dedicated to scaling the AI infrastructure that powers cutting-edge data science applications. Our team solves complex challenges across datacenter hardware, networking, distributed systems, and software deployment. We collaborate closely to design and deliver leading infrastructure solutions. We value strong technical foundations paired with creative thinking and a bias toward execution. Together, we continuously push boundaries, grow our skills, and advance NVIDIA’s capacity to build and deploy AI-based infrastructure at scale.\nWhat you will be doing:\nContribute to a comprehensive platform that automates GPU asset provisioning, configuration, and lifecycle management across cloud providers.\nBuild end-to-end automation of data center management, break/fix, and the full span of system upkeep for large-scale Machine Learning systems. \nImplement monitoring and health management capabilities that enable industry-leading reliability, availability, and scalability of GPU assets.\nHarness multiple data streams, ranging from GPU hardware diagnostics to cluster and network telemetry.\nBuild automated test infrastructure that we use to qualify distributed systems for operation.\nPartner with engineering teams across NVIDIA to ensure the software integrates seamlessly from the hardware all the way up to the AI training applications.\nWhat we need to see:\n12+ years of experience in a similar role working on large-scale production systems.\nBS in Computer Science/Engineering/Physics/Mathematics or other comparable degree, or equivalent experience.\nExpert level knowledge of a systems programming language (Go, Python, and/or Rust) and a solid understanding of Data Structures and Algorithms.\nStrong background in Linux system administration and management.\nDeep knowledge of container orchestration platforms such as Kubernetes and/or SLURM. \nUnderstanding of performance, security, and reliability in complex distributed systems.\nFamiliarity with system level architecture, data synchronization, fault tolerance, and state management.\nWays to stand out from the crowd:\nProficiency in designing and building widespread distributed networks. \nExperience managing large-scale distributed systems independently of cloud providers.\nExtensive expertise in datacenter operations and GPU hardware. \nHands-on experience working with RDMA networking.\nAdvanced hands-on experience and deep understanding of cluster management systems (Kubernetes, SLURM).\nYour base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 224,000 USD - 356,500 USD for Level 5, and 272,000 USD - 431,250 USD for Level 6.You will also be eligible for equity and benefits.\nApplications for this job will be accepted at least until October 31, 2026.This posting is for an existing vacancy.\nNVIDIA uses AI tools in its recruiting processes.\nNVIDIA is committed to fostering an inclusive work environment and proud to be an equal opportunity employer. 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