Member of Engineering – Compute

poolside

Optimize GPU utilization and deliver stable inference serving for researchers in AI development. Collaborate with multiple teams to enhance research velocity with effective management systems.

Posted 7/15/2026full-timeRemote • 🇪🇺 Anywhere in EuropeMid-LevelSeniorWebsite

Core Competencies

Role fit

Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in designing and developing systems for GPU workload management, with a strong focus on observability and debuggability. Proficient in building APIs and tooling for efficient model deployment and inference serving in high-throughput environments.

Highest-signal resume keywords

Programming Skills In GoSystems Engineering BackgroundProduction Experience With Kubernetes InternalsExperience In Large Scale Inference RequestsBias Toward Observability And Debuggability

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Programming Skills In GoDistributed SystemsSchedulersControl PlanesHigh-Throughput Data PlanesKubernetes InternalsAPI DevelopmentTooling DevelopmentModel DeploymentInference Request Serving

Tools & Technologies

Kubernetes

Industry Keywords

GPU UtilizationWorkload ManagementDebugging Production IssuesResearch Velocity

Tech Stack

Tools & technologies

Distributed SystemsGoKubernetes

About the role

Key responsibilities & impact

Design and develop internal scheduling system to maximize GPU utilization
Build API and tooling to help manage the lifecycle of GPU workloads and troubleshoot failures
Design and improve inference control plane to speed up model deployment and inference request serving
Collaborate with research to improve research velocity continuously

Requirements

What you’ll need

Strong programming skills in Go, or other similar languages
Strong systems engineering background: distributed systems, schedulers, control planes, or high-throughput data planes.
Production experience with Kubernetes internals — controllers, informers, operators — not just deploying to it.
Bias toward observability and debuggability: building a system that is easy to navigate when debugging production issues
Plus: experience in systems serving large scale inference requests

Benefits

Comp & perks

Fully remote work & flexible hours
37 days/year of vacation & holidays
Health insurance allowance for you & dependents
16 weeks of flexible, full-pay parental leave
Well-being, always-be-learning & home office allowances
Company-provided equipment
Frequent team get togethers
Diverse & inclusive people-first culture
Diverse & inclusive people-first culture