Senior GPU Engineer, Cloud AI Infrastructure & Performance

WebHosting; United States; Remote; USD 190,000 - 210,000; Full time

Benefits offered by this job

Insurance premiums

401(k) match

Development stipend

Holidays + PTO

Sabbatical program

Remote setup allowance

Internet reimbursement

Gym membership

Wellable subscription

Job summary

Vultr is seeking a highly skilled Senior GPU Engineer to design, optimize, and scale GPU infrastructure for AI training and inference workloads. You will own end-to-end system performance from hardware qualification to cluster-level optimization and mentor teammates.

The role emphasizes deep GPU systems experience, distributed performance tuning, and leadership across cross-functional teams in a fast-growing cloud company.

Qualifications

• Deep experience with GPU systems and AI workloads.
• Proven ability to lead engineering initiatives.
• Strong collaboration across cross-functional teams.

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.

Skills

GPU systems

Distributed performance tuning

Leadership & mentoring

Tools

NCCL

Job description

Vultr is seeking a highly skilled Senior GPU Engineer to design, optimize, and scale GPU infrastructure for AI training and inference workloads. You will own end-to-end system performance from hardware qualification to cluster-level optimization and mentor teammates.

The role emphasizes deep GPU systems experience, distributed performance tuning, and leadership across cross-functional teams in a fast-growing cloud company.