{"id":1975998,"url":"https://alion.io/job/constant-senior-gpu-engineer","title":"Senior GPU Engineer","company":{"id":1786392,"name":"Constant","domain":"constant.com","url":"https://alion.io/company/constant-com","size_band":"501-1000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Ashby","truth_index":{"grade":"B","score":79,"open_postings":13,"ghost_share":0,"stale_share":0.846,"repost_share":0,"time_to_fill_p50_days":45,"computed_at":"2026-10-08T05:49:30Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":"senior","employment_type":"full_time","work_mode":"remote","remote_scope":"stated_countries","remote_scope_basis":"posting_text","remote_working_hours":null,"hiring_geo_confidence":"structured","locations":[],"countries":[],"hiring_countries":["US"],"hiring_countries_total":1,"salary":{"min":190000,"max":210000,"currency":"USD","period":"year","gross":null,"usd_annual":210000},"salary_estimate":null,"experience_years_min":5,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Ansible","optional":false},{"name":"HPC","optional":false},{"name":"Linux","optional":false},{"name":"NCCL","optional":false},{"name":"Python","optional":false},{"name":"Vultr","optional":false}],"status":"live","first_seen_at":"2026-10-06T20:03:12Z","employer_posted_date":"2026-10-06","last_verified_at":"2026-10-09T00:57:45Z","board_verified":true,"closed_at":null,"days_open":2,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":2},"description":"Who We Are\nVultr is on a mission to make high-performance cloud infrastructure easy to use, affordable, and locally accessible for enterprises and AI innovators around the world. With 33 global cloud data center locations, Vultr is trusted by hundreds of thousands of active customers across 185 countries for its flexible, scalable, global Cloud Compute, Cloud GPU, Bare Metal, and Cloud Storage solutions. In December 2024 Vultr announced an equity financing at a $3.5 billion valuation. Founded by David Aninowsky and self-funded for over a decade, Vultr has grown to become the world’s largest privately-held cloud infrastructure company.\nVultr Cares\n100% company-paid insurance premiums for employee medical, dental and vision plans.\n\n401(k) plan that matches 100% up to 4%, with immediate vesting\n\nProfessional Development Reimbursement of $2,500 each year\n\n11 Holidays + Paid Time Off Accrual + Rollover Plan\n\nCommitment matters to Vultr! Increased PTO at 3 year and 10 year anniversary + 1 month paid sabbatical every 5 years + Anniversary Bonus each year\n\n$500 stipend for remote office setup in first year + $400 each following year\n\nInternet reimbursement up to $75 per month\n\nGym membership reimbursement up to $50 per month\n\nCompany paid Wellable subscription\n\nJoin Vultr\nVultr is seeking a highly skilled and experienced Senior GPU Engineer to design, optimize, and scale GPU infrastructure for AI training and inference workloads. The ideal candidate is deep experience with GPU systems, distributed performance tuning, and leading engineering initiatives across cross-functional teams. This is a highly visible role in a high-growth technology company, which will require ownership of end-to-end system performance, from hardware qualification to cluster-level optimization, and the ability to mentor and elevate team capabilities. This is your opportunity to join our fast growing team and leave your mark on Vultr and the future of Cloud Infrastructure.\nKey Responsibilities\nOwn end-to-end validation of GPU clusters and new hardware platforms\n\nLead hardware qualification and bring-up for new GPU platforms\n\nAnalyze and resolve performance bottlenecks across GPU, CPU, PCIe, and network layers\n\nEstablish and maintain validation frameworks, test suites, and performance baselines\n\nDevelop and enhance automation frameworks for cluster provisioning and validation\n\nDefine performance baselines and validation methodologies\n\nTroubleshoot complex distributed system issues, including communication libraries (e.g., NCCL)\n\nImprove system reliability through proactive testing and tuning\n\nMentor engineers and elevate team capabilities\n\nDrive cross-functional initiatives to improve GPU cluster reliability and efficiency\n\nQualifications\n5+ years of experience in GPU infrastructure, HPC, or distributed systems\n\nStrong expertise in Linux systems and server hardware\n\nProven experience with large-scale GPU clusters\n\nStrong programming skills in Python (beyond basic scripting)\n\nExperience with automation frameworks (Ansible or similar)\n\nExperience defining validation standards and performance baselines for GPU infrastructure\n\nStrong debugging skills across system layers (hardware → OS → network)\n\nFamiliarity with high-speed networking concepts to coordinate with fabric engineering teams\n\nExcellent communication and cross-team collaboration skills\n\nCompensation\n$190,000 - $210,000\nFinal compensation will vary depending on years of experience, background/skill set, location, and applicable laws.\nInclusion & Privacy\nWe are an equal opportunity employer and are committed to creating an inclusive environment for all employees. We welcome applications from individuals of all backgrounds and experiences, and we prohibit discrimination based on race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, veteran status, or any other protected status under applicable laws. Vultr will consider qualified applicants with arrest or conviction records in accordance with applicable laws and will not conduct a background check until after an offer of employment has been extended and accepted.\nWe also take your privacy seriously. We handle personal information responsibly and follow applicable laws, including U.S. privacy rules and India’s Digital Personal Data Protection Act, 2023. Your data is used only for legitimate business purposes and is protected with proper security measures.\nWhere allowed by law, applicants may request details about the data we collect, access or delete their information, withdraw consent for its use, and opt out of nonessential communications. 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