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poolside

Develops AI tools for software development

Member of Engineering - Inference Infrastructure

Applied Machine LearningConfirmed live in the last 24 hours
Full-timeNo salary listed

About the Job

Requirements

  • Strong programming skills in Go or a similar language.
  • A strong systems engineering background in distributed systems, schedulers, control planes, or high-throughput data planes.
  • Production experience with Kubernetes internals, including controllers, informers, and operators, rather than only deploying to Kubernetes.
  • A focus on observability and debuggability, including building systems that are easy to navigate when investigating production issues.

Responsibilities

  • Design and develop an internal scheduling system to maximize GPU utilization.
  • Build APIs and tooling to manage the lifecycle of GPU workloads and troubleshoot failures.
  • Design and improve the inference control plane to accelerate model deployment and inference request serving.
  • Collaborate with research to continuously improve research velocity.

Desired Qualifications

  • Experience serving large-scale inference requests.

About the Company

poolside

Develops AI tools for software development

Poolside.ai builds AI-powered tools to help with software development. Its products assist coding and software design for developers, with the long-term aim of enabling anyone, even those without technical skills, to build software through AI-guided, human-assisted interactions. The tools work by providing AI that can understand problems, reason about solutions, and plan development steps, delivered via a subscription model that gives customers access to the software and services (with potential for licensing the technology to others). The company differentiates itself by pursuing democratization of software creation—making AI-assisted coding and design accessible to a broader audience—and by combining automated AI capabilities with human guidance. Its goal is to make software development faster and cheaper, expand AI-driven creation into other fields, and scale its capabilities through ongoing iterations and licensing opportunities.

Company size
201-500
Company stage
Growth Equity (Venture Capital)
Total funding
$1.6B
Headquarters
Paris, France
Founded
2023

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