Senior GPU Engineer

🕒 October 6

🇺🇸 United States – Remote

💵 $190k - $210k / year

⏰ Full Time

🟠 Senior

👷🏻‍♀️ Engineer

👻 Ghost score 3%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

Apply Now

Find Similar Remote Jobs

Set Up Email Alert For New Jobs

📊 Check your resume score for this job

Improve your chances of getting an interview by checking your resume score before you apply.

Upload Resume

Vultr

WebsiteLinkedInAll Job Openings

201 - 500 employees

Founded 2014

🤖 Artificial Intelligence

🤝 B2B

🔧 Hardware

💰 $329M Debt Financing - Vultr on 2025-06

Artificial Intelligence • B2B • Hardware

Vultr is a global cloud infrastructure provider offering on-demand virtual machines, bare-metal servers, GPU-accelerated instances, managed databases, object and block storage, Kubernetes, and networking services. The platform emphasizes AI and HPC workloads with a broad selection of AMD and NVIDIA GPUs, fast networking, and 32+ data center regions, plus a marketplace of deployable apps and developer-friendly APIs. Vultr targets developers and businesses seeking affordable, scalable, and compliant cloud compute and storage alternatives to hyperscalers.

📋 Description

• Design, optimize, and scale GPU infrastructure for AI training and inference workloads • 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 such as 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

🎯 Requirements

• 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 • Excellent communication and cross-team collaboration skills • Located in the United States • Legally authorized to work in the United States • Must answer whether employment visa sponsorship is required

🏖️ Benefits

• 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 • 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