Senior GPU Platform Engineer

Zesty

. Design and deliver GPU optimization capabilities, including improved GPU utilization, intelligent resource allocation, workload scheduling and cost efficiency .

Posted 10/25/2026full-timeTel Aviv-Yafo • IsraelSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in GPU optimization, including resource allocation and workload scheduling, while delivering high-quality production code. Proven ability to collaborate with stakeholders to enhance GPU infrastructure efficiency and cost-effectiveness.

Highest-signal resume keywords

GPU OptimizationKubernetes ExperienceProduction-Quality CodeGPU FinOps PracticesNVIDIA GPU Operator

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

GPU UtilizationWorkload SchedulingResource AllocationCost EfficiencyProduction Code WritingKubernetes OperatorsGPU Workloads OptimizationCapacity PlanningTime-SlicingDCGM

Soft Skills

CollaborationProblem-Solving

Tools & Technologies

AI-Powered Development ToolsNVIDIA GPU OperatorDCGMMIG

Industry Keywords

DevOpsPlatform EngineeringGPU InfrastructureChargebackShowback

Tech Stack

Tools & technologies

Kubernetes

About the role

Key responsibilities & impact

Design and deliver GPU optimization capabilities, including improved GPU utilization, intelligent resource allocation, workload scheduling and cost efficiency
Own complex features end-to-end, from technical design through production delivery
Translate real-world GPU infrastructure challenges into practical software solutions
Collaborate with R&D and product stakeholders to deliver reliable, high-impact product capabilities
Write clean, maintainable production code using AI-powered development tools
Build product capabilities that help teams run GPU workloads more efficiently, reliably and cost-effectively

Requirements

What you’ll need

More than 5 years of hands-on DevOps or Platform Engineering experience
Proven production experience optimizing GPU infrastructure or GPU workloads
Strong Kubernetes experience
Demonstrated ability to write production-quality code
Evidence of measurable improvements in GPU utilization, performance, scheduling, allocation, capacity, reliability or cost efficiency
Experience with NVIDIA GPU Operator, DCGM, MIG, GPU sharing or time-slicing is a plus
Experience developing Kubernetes operators, controllers or scheduling-related components is a plus
Experience with GPU FinOps practices, including cost visibility, chargeback/showback, right-sizing or capacity planning is a plus

Benefits

Comp & perks

Full-time employment
Opportunity to take ownership and share ideas openly
Direct influence on product capabilities
Work on challenging cloud-native problems within an R&D team
Collaborative team environment
AI-powered development tools to accelerate delivery, improve code quality, and streamline code reviews