Senior GPU Engineer
This is the employer's own posting, not a copy on a job board.
What we know
Is it still open?
Confirmed still open
Last checked 1d ago — checked against the employer's own applicant tracking system, which is the company answering directly.
We re-read the employer's own applicant tracking system and the posting was still there. That is the company answering directly.
How old is it?
Posted 4d ago
The date the source published, not the day we noticed it (2026-10-06). Last seen at its source 2h ago.
We have tracked this listing since 6 Oct 2026 (4 days). The employer's own board has carried it every time we have read it, most recently 2 hours ago.
Is it remote?
Remote - United States
That is the location the employer filed this posting under. Quoted as written — we do not re-word the source's own location.
Who may apply?
United States
The description states no restriction of its own. This is the source's own tag.
Pay
$190k–210k/yr
Read out of the job description by us, not from a structured field. Shown in the posting's own currency and period; we never convert.
Skills named in the ad
Recognised terms only, from a fixed vocabulary — this is what CV matching compares against.
Carried by 1 source
-
Ashby employer's own board first seen 4d ago · last seen 2h ago
The listing
Who We Are
Vultr 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.
Vultr Cares
100% company-paid insurance premiums for employee medical, dental and vision plans.
401(k) plan that matches 100% up to 4%, with immediate vesting
Professional Development Reimbursement of $2,500 each year
11 Holidays + Paid Time Off Accrual + Rollover Plan
Commitment matters to Vultr! Increased PTO at 3 year and 10 year anniversary + 1 month paid sabbatical every 5 years + Anniversary Bonus each year
$500 stipend for remote office setup in first year + $400 each following year
Internet reimbursement up to $75 per month
Gym membership reimbursement up to $50 per month
Company paid Wellable subscription
Join Vultr
Vultr 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.
Key Responsibilities
Own end-to-end validation of GPU clusters and new hardware platforms
Lead hardware qualification and bring-up for new GPU platforms
Analyze and resolve performance bottlenecks across GPU, CPU, PCIe, and network layers
Establish and maintain validation frameworks, test suites, and performance baselines
Develop and enhance automation frameworks for cluster provisioning and validation
Define performance baselines and validation methodologies
Troubleshoot complex distributed system issues, including communication libraries (e.g., NCCL)
Improve system reliability through proactive testing and tuning
Mentor engineers and elevate team capabilities
Drive cross-functional initiatives to improve GPU cluster reliability and efficiency
Qualifications
5+ years of experience in GPU infrastructure, HPC, or distributed systems
Strong expertise in Linux systems and server hardware
Proven experience with large-scale GPU clusters
Strong programming skills in Python (beyond basic scripting)
Experience with automation frameworks (Ansible or similar)
Experience defining validation standards and performance baselines for GPU infrastructure
Strong debugging skills across system layers (hardware → OS → network)
Familiarity with high-speed networking concepts to coordinate with fabric engineering teams
Excellent communication and cross-team collaboration skills
Compensation
$190,000 - $210,000
Final compensation will vary depending on years of experience, background/skill set, location, and applicable laws.
Inclusion & Privacy
We 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.
We 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.
Where 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. For more details, please see our Privacy Policy.