Member of Engineering (Inference Infrastructure)
Poolside· Engineering
RemoteFull-timePosted 2mo ago
About the role
Role focused on GPU workload scheduling and inference serving optimization to improve throughput and latency for evals, reinforcement learning, and large-scale training stability; collaboration across inference, scalability, infra, and research teams to enhance research velocity and GPU utilization.
Responsibilities
- 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
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
- Plus: experience in systems serving large scale inference requests
Skills
Required:GoDistributed systemsKubernetes internalsObservability
Nice to have:Inference serving at scale
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
Last updated Oct 4, 2026. Interested? Apply on the company site.
About Poolside
We build the models. You build the future.
Poolside is a foundation model company bringing intelligence to everywhere work gets done. Our mission is to drive abundance for humanity by creating artificial general intelligence.
Data and KnowledgeDelivering intelligence across your development ecosystemDeveloper SurfacesFoundation ModelsFoundational AIMulti-Agent Orchestrationagentsliquid-ai-recruiting-target
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