{"id":43821,"url":"https://alion.io/job/nvidia-senior-hpc-cluster-engineer-ai-ml","title":"Senior HPC Cluster Engineer - AI, ML","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":778,"ghost_share":0.026,"stale_share":0.725,"repost_share":0.041,"time_to_fill_p50_days":33,"computed_at":"2026-10-20T05:45:00Z"}},"role":"AI/ML","role_family":"AI/ML","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":["Bengaluru, India","Pune, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":33000,"max_usd":67000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":38},"experience_years_min":5,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Ansible","optional":false},{"name":"CentOS Stream","optional":false},{"name":"Configuration Management","optional":false},{"name":"CUDA","optional":false},{"name":"CUDA Toolkit","optional":false},{"name":"Docker","optional":false},{"name":"HPC","optional":false},{"name":"InfiniBand","optional":false},{"name":"Kubernetes","optional":false},{"name":"Linux","optional":false},{"name":"MPI","optional":false},{"name":"NCCL","optional":false},{"name":"Podman","optional":false},{"name":"Puppet","optional":false},{"name":"Python","optional":false},{"name":"PyTorch","optional":false},{"name":"SLI/SLO/SLA","optional":false},{"name":"SLURM","optional":false},{"name":"TensorFlow","optional":false},{"name":"Terraform","optional":false},{"name":"Ubuntu","optional":false},{"name":"C","optional":true}],"status":"live","first_seen_at":"2026-08-06T00:00:00Z","employer_posted_date":"2026-08-06","last_verified_at":"2026-10-20T10:17:06Z","board_verified":true,"closed_at":null,"days_open":75,"trust":{"level":"ok","repost_count":1,"flags":[],"days_open":75},"description":"NVIDIA is a pioneer in accelerated computing, known for inventing the GPU and driving breakthroughs in gaming, computer graphics, high-performance computing, and artificial intelligence. Our technology powers everything from generative AI to autonomous systems, and we continue to shape the future of computing through innovation and collaboration. Within this mission, our team, Managed AI Superclusters (MARS) builds and scales the infrastructure, platforms, and tools that enable researchers and engineers to develop the next generation of AI/ML systems. By joining us, you’ll help design solutions that power some of the world’s most advanced computing workloads.\nNVIDIA is looking for a Senior AI/ML HPC Cluster Engineer to join our MARS team. You will provide leadership and strategic guidance on the management of large-scale HPC systems including the deployment of compute, networking, and storage. You will be working with a team of passionate and skilled engineers across NVIDIA that are continuously working to provide better tools to build and manage this infrastructure. Ideal candidate is strong in building and maintaining distributed clusters, driving improvements, and has the ability to understand researcher computing needs.\nWhat you'll be doing:\nProvide leadership in systems administration and service delivery on our AI/HPC fleet by coordinating system upgrades, responding to incidents, and delivering reliability improvements.\n\nCollaborate closely with global teams to deliver a world class user experience in AI and HPC research.\n\nOwn day-to-day operations of production AI/HPC clusters, ensuring system health, user satisfaction, and efficient resource utilization.\n\nDevelop and improve our ecosystem around GPU-accelerated computing including developing scalable automation solutions.\n\nBuild and maintain heterogeneous AI/ML clusters on-premises and in the cloud.\n\nCreate and cultivate customer and cross-team relationships to meet user evolving user needs.\n\nSupport our researchers to run their workloads including performance analysis and optimizations\n\nAnalyze and optimize cluster efficiency, job fragmentation, and GPU waste to meet internal SLA targets.\n\nConduct root cause analysis and suggest corrective action Proactively find and fix issues before they occur.\n\nLead SEV triage and postmortems for reliability incidents affecting users or infrastructure.\n\nParticipate in on-call rotation and incident response for critical production GPU clusters.\n\nWhat we need to see:\nBachelor’s degree in Computer Science, Electrical Engineering or related field or equivalent experience\n\nMinimum 5 years of experience designing and operating large scale compute infrastructure\n\nExperience with AI/HPC advanced job schedulers, such as Slurm, K8s, PBS, RTDA, BCM, or LSF\n\nProficient in administering Centos/RHEL and/or Ubuntu Linux distributions\n\nSolid understanding of cluster configuration management tools (BCM, Terraform, Ansible, Puppet, Salt, etc.), container technologies (Docker, Singularity, Podman, Shifter, 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