2026 PhD Software Engineer Intern (Container Platform), United States

Job Description

We're looking for PhD candidates to intern on the Container Platform team during summer of 2026 (12 weeks). You will be embedded in our engineering team and work closely with other Software Engineers and Engineering leads. As a PhD intern, you will contribute to research and development of software and algorithms responsible for continuous predictive auto-scaling of Compute resources allocated to all of Uber's workloads and the underlying Compute clusters. You'll design and develop mechanisms to optimize and improve accuracy of Compute capacity autoscaling, thus improving efficiency as well as reliability of our Compute infrastructure.

About the Team:

The Container Platform team's mission is to build the next generation of Uber's container orchestration platform on Kubernetes that is secure, reliable, scalable, and highly efficient. At Uber we have a complex infrastructure spanning both on-prem data centers and cloud. It supports a diverse variety of workloads (stateless, batch, streaming, ML/AI, stateful), each different in its characteristics and requirements.

We build solutions to enable user applications/jobs to be deployed anywhere in the world with the touch of a button. We build abstractions so that Uber developers do not have to care about infrastructure and infrastructure just works for every application type. Given our massive scale, we continuously push the limits of efficiency while ensuring reliability. We actively work with the open-source community including Kubernetes and contribute back. We are at the cutting edge of technology and the team regularly presents at industry conferences.

Here are some KubeCon sessions (2024 session + video, 2023 session1, session2) where we have talked about our team's work.

What You'll Do

• Design and implement solutions to meet Platform goals
• Write maintainable and extensible code with high quality tests and documentation
• Collaborate with other engineering teams as part of project design and execution
• Productionize solutions across the fleet by having right observability for close monitoring and evolving the solution based on production experience.

• Current PhD student in Computer Science, Artificial Intelligence, or related field
• Candidates must have at least one semester/quarter of their education left following the internship

• Experience programming in one or more languages like Go, Java, Python, C/C++
• Demonstrated ability to conduct independent research
• Background in large-scale backend infrastructure and Distributed Systems
• Knowledge of cluster management solutions such as Kubernetes
• Strong problem-solving and communication skills