The Fleet Scheduling team builds interfaces and systems that help researchers manage AI workloads across some of the world’s largest supercomputing clusters. The team focuses on real-time visibility, resource tracking, scheduling, operational efficiency, and making complex infrastructure usable.

About the role

This Full Stack Engineer designs, develops, and operates web-based systems for monitoring, scheduling, and managing large-scale AI workloads. The role works closely with research, product, and infrastructure teams and combines intuitive user interfaces with scalable backend systems.

Responsibilities

• Design and develop full-stack web applications for tracking, monitoring, and managing AI workloads in real time.
• Translate researcher and infrastructure needs into intuitive interfaces and scalable backend services.
• Build scheduling, resource-management, and operational tooling for large supercomputing clusters.
• Improve system transparency, reliability, performance, observability, and operational workflows.
• Design systems that scale to extremely large workloads while keeping the user experience responsive and understandable.
• Collaborate across research and infrastructure teams to ship production tools and continuously improve them.

Qualifications

• Full-stack web engineering experience with modern frontend frameworks such as React, Vue, or Angular.
• Backend experience with Python, Go, Node.js, or similar technologies.
• Experience with APIs, GraphQL, distributed systems, infrastructure, and Kubernetes is valuable.
• Strong systems thinking and interest in high-scale compute infrastructure.