Job Description
A role focused on developing a dynamic resource allocation system to optimize cloud infrastructure efficiency, enhance user productivity, and streamline workflows by provisioning GPU VMs within a Kubernetes environment.
Key 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 VM provisioning and lifecycle management into the in-house ML Scheduler
Requirements
- Currently pursuing a Bachelor’s or Master’s degree in Computer Science or related field and graduating before December 2026
- Proficient in Machine Learning concepts and applications
- Familiarity with Google Kubernetes Engine (GKE) and cloud resource management
- Develop the ability to create a system to provide users with GPU VMs for their development environment
- Develop a dynamic VM allocation mechanism integrated into a shared Google Kubernetes Engine (GKE) resource pool
- Integrate the VM provisioning and lifecycle management system into the in-house ML Scheduler
- Demonstrate outstanding problem-solving abilities coupled with great attention to detail
- Possess excellent interpersonal and communication skills
Benefits & Perks
Compensation/salary range (not specified in the posting)
Work schedule (not specified in the posting)
Work environment perks (inclusive and diverse workplace, psychological safety, equal opportunity employment)
Additional benefits (fostering inclusion, commitment to diversity)
Ready to Apply?
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