GPU Performance and Benchmarking Engineer

Vultr

GPU Performance Engineer driving performance validation and optimization of GPU infrastructure at Vultr. Collaborating with engineers to enhance AI/ML workload efficiency and throughput.

Posted 7/13/2026full-timeRemote • 🇺🇸 United StatesMid-LevelSenior💰 $140,000 - $150,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in GPU performance engineering, including benchmarking, profiling, and tuning for AI/ML workloads. Proficient in developing automation tools and methodologies to validate performance across various GPU platforms.

Highest-signal resume keywords

GPU Performance EngineeringBenchmarking Tools (NVIDIA Nsight, DCGM, MLPerf)Python Scripting for BenchmarkingAI/ML Workload Performance AnalysisPerformance Tuning Across GPU and CUDA

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

GPU ProfilingPerformance BenchmarkingWorkload Parameter TuningData AnalysisPerformance Baseline Establishment

Soft Skills

Analytical SkillsWritten Communication

Tools & Technologies

NVIDIA NsightDCGMNccl-testsMLPerfGPU-Burn

Industry Keywords

AI/ML Workload CharacteristicsHigh-Performance Computing (HPC)NVIDIAAMDInfiniBand

Tech Stack

Tools & technologies

LinuxPython

About the role

Key responsibilities & impact

Design and execute performance benchmarks for AI training and inference workloads
Profile and characterize GPU workloads to identify performance bottlenecks and optimization opportunities
Systematically tune workload parameters (batch size, precision, parallelism, memory, etc.) to maximize throughput
Establish and maintain performance baselines and success criteria across GPU platforms
Develop benchmarking tools, scripts, and automation for repeatable performance validation
Analyze and report benchmark results with actionable recommendations for engineering teams
Validate performance of new GPU hardware platforms before production deployment
Collaborate with GPU Engineers and Fabric Engineers to correlate performance with system-level health
Track and evaluate emerging GPU architectures and software releases for performance impact
Document benchmarking methodologies, tuning playbooks, and performance best practices

Requirements

What you’ll need

3–7 years of experience in GPU performance engineering, benchmarking, or HPC
Hands-on experience with GPU profiling and benchmarking tools (e.g., NVIDIA Nsight, DCGM, nccl-tests, MLPerf, GPU-Burn)
Strong understanding of AI/ML workload performance characteristics (training vs. inference, batch sizing, precision modes)
Experience tuning performance parameters across GPU, CUDA, and framework layers
Familiarity with major GPU platforms (NVIDIA, AMD) and their performance tooling
Proficiency in Python for benchmark scripting and data analysis
Basic understanding of Linux systems and server hardware
Familiarity with high-speed networking concepts (InfiniBand, RoCE, NCCL) and their impact on distributed performance
Strong analytical skills with the ability to translate data into clear recommendations
Excellent written communication skills for performance reports and documentation

Benefits

Comp & perks

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