Member of Engineering (Inference Infrastructure)

The role

You will work in the compute team focusing on GPU workload scheduling and inference serving optimization. You will design internal scheduling systems and improve the inference control plane to maximize GPU utilization.

What you will do

• 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

Required qualifications

• 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

Nice to have

• experience in systems serving large scale inference requests

Benefits

• 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

Before you apply

• Intro call with a member of our team
• Technical Interview(s) with one of our Members of Engineering
• Team fit call with the People team
• Final interview with one of our Founding Engineers

About the company

Poolside exists to build a world where AI will be the engine behind economically valuable work and scientific progress. The team is distributed across Europe and North America.