About The Position

We are looking for an ambitious and talented individual who is keen on applying their skills to real-life AI infrastructural issues. In this role, you will have the opportunity to contribute to the building of a dynamic resource allocation system designed to enhance efficiency and productivity. This project is key to eliminating resource contention and optimizing our cloud infrastructure costs. The goal here is to ensure development VMs are provisioned and consumed as needed, based on the lifecycle defined by the user. Beyond system efficiency gains, this project will increase user productivity by eliminating resource access bottlenecks, allowing engineers to instantly provision machines for every task, streamlining workflows, and accelerating project completion. About the Work Develop a system to provide users with GPU VMs for their development environment. Create a dynamic VM allocation mechanism integrated into a shared Google Kubernetes Engine (GKE) resource pool. Integrate into our in-house ML Scheduler for VM provisioning and lifecycle management.

Requirements

  • Currently pursuing a Bachelor's or Master's degree in Computer Science or related field and graduating in/before December 2026
  • Proficient in Machine Learning concepts and applications.
  • Familiarity with Google Kubernetes Engine (GKE) and cloud resource management.
  • Outstanding problem-solving abilities coupled with great attention to detail.
  • Excellent interpersonal and communication skills.

Responsibilities

  • Develop a system to provide users with GPU VMs for their development environment.
  • Create a dynamic VM allocation mechanism integrated into a shared Google Kubernetes Engine (GKE) resource pool.
  • Integrate into our in-house ML Scheduler for VM provisioning and lifecycle management.
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