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](https://kccncna2024.sched.com/event/1i7qJ/share-the-ride-robust-multi-tenancy-in-kubernetes-at-uber-sashank-appireddy-apoorva-jindal-uber) \+ [video](https://youtu.be/ka5oMGh2EiU?si=52dmd7pnOUIAbnZ_), 2023 [session1](https://kccncna2023.sched.com/event/1R2qt/on-the-right-tack-kubernetes-at-uber-scale-aditya-bhave-apoorva-jindal-uber-technologies), [session2](https://kccncna2023.sched.com/event/1R2qq/efficient-resource-utilization-for-batch-compute-on-kubernetes-amit-kumar-kevin-xu-uber)) 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. **Basic Qualifications** - 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 **Preferred Qualifications** - 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 For Sunnyvale, CA-based roles: The base hourly rate amount for this role is USD$67.00 per hour. You will also be eligible for various benefits. Uber's mission is to reimagine the way the world moves for the better. Here, bold ideas create real-world impact, challenges drive growth, and speed fuels progress. What moves us, moves the world - let's move it forward, together. Uber is proud to be an Equal Opportunity employer. All qualified applicants will receive consideration for employment without regard to sex, gender identity, sexual orientation, race, color, religion, national origin, disability, protected Veteran status, age, or any other characteristic protected by law. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. If you have a disability or special need that requires accommodation, please let us know by completing [this form](https://forms.gle/aDWTk9k6xtMU25Y5A). Offices continue to be central to collaboration and Uber’s cultural identity. Unless formally approved to work fully remotely, Uber expects employees to spend at least half of their work time in their assigned office. For certain roles, such as those based at green-light hubs, employees are expected to be in-office for 100% of their time. Please speak with your recruiter to better understand in-office expectations for this role.