Job Description
A role focused on developing a dynamic resource allocation system to optimize cloud infrastructure, improve efficiency, and streamline workflows for AI development at a self-driving technology company.
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
- Have great attention to detail
- Possess excellent interpersonal and communication skills
Benefits & Perks
Compensation/salary range not specified
Work schedule not specified
Work environment perks not specified
Opportunities to work on cutting-edge AI infrastructure projects
Potential for professional development in cloud resource management and machine learning
Ready to Apply?
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