{"id":68324,"url":"https://alion.io/job/vast-ai-hpc-gpu-infrastructure-support-engineer","title":"AI, HPC & GPU Infrastructure Support Engineer","company":{"id":26005,"name":"Vast.ai","domain":"vast.ai","url":"https://alion.io/company/vast","size_band":null,"is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Ashby","truth_index":{"grade":"C","score":68,"open_postings":15,"ghost_share":0.533,"stale_share":0,"repost_share":0,"time_to_fill_p50_days":null,"computed_at":"2026-10-16T05:45:00Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":null,"employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Los Angeles, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":{"min":90000,"max":150000,"currency":"USD","period":"year","gross":null,"usd_annual":150000},"salary_estimate":null,"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Bash","optional":false},{"name":"CentOS Stream","optional":false},{"name":"CUDA","optional":false},{"name":"CUDA Toolkit","optional":false},{"name":"Debian","optional":false},{"name":"DHCP","optional":false},{"name":"DNS","optional":false},{"name":"Docker","optional":false},{"name":"Docker Compose","optional":false},{"name":"KVM","optional":false},{"name":"Linux","optional":false},{"name":"Proxmox VE","optional":false},{"name":"Python","optional":false},{"name":"PyTorch","optional":false},{"name":"TensorFlow","optional":false},{"name":"Ubuntu","optional":false},{"name":"VLAN","optional":false},{"name":"VMWare","optional":false},{"name":"VPN","optional":false},{"name":"Grafana","optional":true},{"name":"LLM","optional":true},{"name":"Prometheus","optional":true}],"status":"live","first_seen_at":"2026-07-30T22:34:01Z","employer_posted_date":"2026-07-30","last_verified_at":"2026-10-17T02:25:49Z","board_verified":true,"closed_at":null,"days_open":78,"trust":{"level":"ok","repost_count":0,"flags":["company_stale"],"days_open":77},"description":"About Us\nVast.ai 's cloud powers AI projects and businesses all over the world. We are democratizing and decentralizing AI computing - reshaping our future for the benefit of humanity. Our mission is to organize, optimize, and orient the world's computation.\nWe value elegance, ownership, integrity, and continuous learning. You'll have the opportunity to dive into state-of-the-art AI systems while collaborating with a globally distributed team.\nAbout the Role\nThis role focuses on troubleshooting complex Linux and GPU infrastructure issues across NVIDIA drivers, CUDA, GPU workloads, Ubuntu, Docker, KVM based virtual machines, networking, hardware, BIOS, and firmware. You’ll investigate failures, reproduce issues, identify root causes, and propose practical solutions across the full infrastructure stack.\nYou’ll also serve as the engineering resource our L1 support team relies on when tickets go beyond frontline triage. You’ll own complex escalations end-to-end, gather technical evidence, coordinate with the appropriate teams, and communicate findings clearly to clients, infrastructure suppliers, and internal teams.\nThe best engineers in this role don’t just resolve individual issues-they recognize recurring patterns, improve diagnostic tooling, and build runbooks that prevent future incidents. You’ll collaborate directly with the engineering and host support teams on systemic Linux, GPU, and infrastructure problems.\nStrong GPU troubleshooting experience, Linux systems knowledge, and technical support skills are the primary requirements. You should be comfortable working autonomously in Ubuntu environments and troubleshooting NVIDIA drivers, CUDA, containers, virtual machines, networking, hardware, and GPU workloads.\nVast.ai users or hosts strongly preferred.\nLocation and Schedule\nThis is a full-time position based in our Westwood, Los Angeles office.\nAvailable schedules:\nMonday-Friday: Fully on-site\n\nSunday-Thursday: Four days on-site and one day working from home\n\nKey Responsibilities\nDiagnose and resolve issues across NVIDIA CUDA/GPU drivers, Docker, and KVM virtualization environments\n\nInvestigate GPU utilization, container resource constraints, thermal throttling, driver conflicts, and disk I/O bottlenecks\n\nAssist clients and infrastructure suppliers working with TensorFlow, PyTorch, and other GPU-accelerated workloads\n\nTroubleshoot network-layer issues, including VLAN, DNS, DHCP, VPN, NAT, firewall rules, and connectivity failures on host machines\n\nHandle escalated support tickets involving GPU workload failures, container issues, networking problems, account infrastructure, and host-side configuration\n\nProvide managed support for supplier onboarding and ongoing machine management, including installation, configuration, and post setup troubleshooting\n\nAdvise suppliers on hardware setup, driver configuration, BIOS and firmware settings, and network configuration for optimal performance\n\nProvide coverage for L1 support overflow during peak periods or incidents\n\nWrite and maintain internal runbooks, escalation guides, and knowledge base articles to reduce repeat escalations\n\nBuild diagnostic and automation tooling in Python and Bash to reduce manual triage overhead\n\nCollaborate with the engineering and support teams to flag and document systemic or recurring platform issues\n\nYou Are\nExperienced with Linux, especially Ubuntu, and comfortable troubleshooting from the command line\n\nSomeone who enjoys debugging difficult problems and fixing broken systems\n\nMethodical and focused on finding root causes, not just temporary fixes\n\nAble to manage complex tickets independently\n\nA clear written communicator with an interest in AI infrastructure and GPU computing\n\nMust-Haves\nStrong Linux systems operations experience with Ubuntu, RHEL/CentOS, or Debian, including networking, storage, services, and permissions\n\nProficiency with Docker, including container debugging, Docker Compose, image management, cgroup limits, and Docker storage and filesystem troubleshooting\n\nExperience with virtualization platforms such as Proxmox VE, VMware, or similar hypervisors, including VM provisioning and troubleshooting\n\nStrong networking fundamentals, including VLANs, DNS, DHCP, NAT, VPNs, firewall rules, and L2/L3 troubleshooting\n\nHands-on experience with NVIDIA GPU drivers, CUDA, and GPU workload troubleshooting\n\nPython and Bash scripting skills for automation and diagnostic tooling\n\nStrong written English communication that is clear, professional, and technically precise\n\nExperience providing technical support in a customer-facing or internal help desk environment\n\nAbility to prioritize across a concurrent queue of escalated tickets, triaging by severity and customer impact, balancing reactive resolution against proactive documentation and tooling work, and making clear judgment calls on when to escalate versus own resolution end-to-end\n\nNice-to-Haves\nFamiliarity with AI/ML frameworks (TensorFlow, PyTorch) and running GPU-accelerated containers\n\nMonitoring and observability experience (Prometheus, Grafana)\n\nRelevant certifications: RHCSA, CompTIA Linux+, or similar\n\nKnowledge of the Vast.ai platform as a client or infrastructure supplier\n\nInterview Process (~1 week)\nAfter you submit your application, our technical team will review your experience and qualifications. Selected candidates will proceed through the following stages:\n15 minutes - Initial Screening (Virtual): A brief conversation about your background, availability, and interest in the role\n\n45 minutes - Experience Interview (Virtual): An introduction to Vast.ai and a deeper discussion of your technical and support experience\n\n2 hours - Meet and Greet and Technical Assessment (On-site): Meet the team and complete an LLM-assisted Linux systems operations assessment\n\nAnnual Salary Range\n$90,000 - $160,000 + equity + benefits\nVast.ai is hiring across all experience levels with compensation commensurate with background, experience and potential.\nBenefits\nComprehensive health, dental, vision, and life insurance\n\n401(k) with company match\n\nMeaningful early-stage equity\n\nOnsite meals, snacks, and close collaboration with founders/tech leaders\n\nAmbitious, fast-paced startup culture where initiative is rewarded","description_format":"text","description_chars":6251,"description_truncated":false,"requirements":{"experience_years_min":null,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":null,"security_clearance":false,"languages":[{"language":"English","level":"Upper-Intermediate (B2)","optional":false}]},"benefits":["Continuous learning","Equity","Life insurance"],"hiring_locations":[],"hiring_excludes":[],"relocation_offered":false,"industries":["Cloud Platforms (IaaS & PaaS)","AI Compute & Inference"],"lifecycle":[{"event":"open","at":"2026-07-30T22:34:01Z"}],"visa":[],"liveness":{"score":6,"band":"cold","label":"Long shot","p_open":1,"p_active":0.222,"p_room":0.28,"age_days":77,"expected_fill_days":21,"reasons":["conf:0","stale_co","win:tail","crowd:"],"computed_at":"2026-10-16T05:45:00Z"},"pay":{"stated_usd_annual":150000,"is_top_pay":false},"html_url":"https://alion.io/job/vast-ai-hpc-gpu-infrastructure-support-engineer","json_url":"https://alion.io/job/vast-ai-hpc-gpu-infrastructure-support-engineer.json","meta":{"generated_at":"2026-10-17T03:54:04Z","cache_seconds":300,"methodology":"https://alion.io/methodology","terms":"https://alion.io/terms","contact":"https://alion.io/contact","api":"https://alion.io/developers","about":"Alion is a live layer of people, companies and AI agents: who they are, whether they are real and active right now, what they do and how to work with them, readable by people and by agents and paid per call.","catalog":"https://alion.io/catalog.json","usage":{"tier":"crawler_verified","counted_by":"address","units_charged":1,"used_today":5111,"day_limit":null,"remaining_today":null,"minute_limit":300,"resets_at":"2026-10-18T00:00:00Z"}},"offers":[{"id":"company.slices","title":"One company in depth, by slice","status":"live","price":{"credits":0.02,"usd":0.002,"plus_per_slice":{"credits":0.05,"usd":0.005}},"unit":"per company, plus each slice with data","note":"the employer in depth","call":{"mcp_tool":"get_company","arguments":{"id":26005},"rest":"https://alion.io/mcp/rest/get_company?id=26005"},"human":"https://alion.io/catalog?offer=company.slices&for=job%2Fvast-ai-hpc-gpu-infrastructure-support-engineer"},{"id":"market.stats","title":"A market slice: pay, demand and time to fill","status":"live","price":{"credits":1,"usd":0.1},"unit":"per slice","note":"pay, demand and time to fill for this role and place","call":{"mcp_tool":"market_stats"},"human":"https://alion.io/catalog?offer=market.stats&for=job%2Fvast-ai-hpc-gpu-infrastructure-support-engineer"},{"id":"job.search","title":"Open jobs by role, technology, place, pay and visa","status":"live","price":{"credits":0.02,"usd":0.002},"unit":"per posting in a list","note":"similar open postings","call":{"mcp_tool":"search_jobs"},"human":"https://alion.io/catalog?offer=job.search&for=job%2Fvast-ai-hpc-gpu-infrastructure-support-engineer"},{"id":"company.verify","title":"Is this company real and active right now","status":"pilot","price":null,"unit":"per company","request":{"url":"https://alion.io/catalog/request","method":"POST","body":"{\"offer\": \"company.verify\", \"for\": \"job/vast-ai-hpc-gpu-infrastructure-support-engineer\", \"note\": \"what you need it for\"}"},"human":"https://alion.io/catalog?offer=company.verify&for=job%2Fvast-ai-hpc-gpu-infrastructure-support-engineer"}]}