GPU Performance and Benchmarking Engineer

🕒 il y a 24 jours

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Vultr

Site WebLinkedInTous les Emplois

201 - 500 employés

Fondée en 2014

🤖 Intelligence artificielle

🤝 B2B

🔧 Matériel

💰 €329 000 000 Debt Financing - Vultr en 2025-06

Artificial Intelligence • B2B • Hardware

Vultr est un fournisseur mondial d'infrastructures cloud offrant des machines virtuelles à la demande, des serveurs bare-metal, des instances accélérées par GPU, des bases de données gérées, un stockage d'objets et de blocs, des services Kubernetes et de mise en réseau. La plateforme met l'accent sur les charges de travail d'IA et de calcul haute performance (HPC) avec un large choix de GPUs AMD et NVIDIA, un réseau rapide, et plus de 32 régions de centres de données, ainsi qu'un marché d'applications déployables et des API conviviales pour les développeurs. Vultr cible les développeurs et les entreprises à la recherche d'alternatives cloud abordables, évolutives et conformes aux hyperscalers pour le calcul et le stockage.

Description

• 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

🎯 Exigences

• 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

🏖️ Avantages

• 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