PhD 2026 Graduate Software Engineer II (AV Labs), United States

About the Role

Uber is launching AV Labs to accelerate the autonomous technology ecosystem. We're building out a high-velocity team of multi-disciplinary experts to turn real-world operations into high-quality data for our autonomous partners. This team is focused on the hardest problem in AV today: unlocking real-world, long-tail driving data. Autonomy is now a data race and Uber has an edge: We collect rare, real-world driving data at a scale and capital efficiency no one else can match.

You will be at the forefront of Physical AI, building advanced autonomy algorithms to add rich semantics to our massive driving data. You will be responsible for the development and implementation of the latest autonomy techniques that enables better data mining, deep scene understanding, and causal modeling of ego vehicle behavior.The ideal candidate will be able to identify complex edge cases, provide robust algorithmic solutions, and set a high technical excellence bar.

What the Candidate Will Do

• Algorithm Development: Develop algorithms that extract high-fidelity semantic meaning from complex urban edge cases to enrich our L4 data lake.
• System Design: Architect onboard systems, including management of upstream sensor dependencies and evaluation metrics for the stack.
• Dataset Optimization: Define the requirements for high-quality large evaluation datasets and objective metrics to evaluate the performance of the system..
• Cross-Functional Collaboration: Partner with platform, product, and security engineering teams to enable the successful deployment of the latest machine learning techniques into production.

Basic Qualifications 

• Completing or recently completed a PhD in Computer Science, Statistics, Mathematics, or a related quantitative field.

Preferred Qualifications

• Proven experience writing clean, maintainable, and high-quality code in a production or collaborative research environment.
• Deep technical expertise in one or more areas of computer science, such as distributed systems, algorithmic design, optimization, or large-scale data processing.
• Documented history of solving complex, unstructured problems through independent research or technical projects.
• Experience designing and crafting scalable, reliable, and reusable software solutions that address complex architectural or algorithmic challenges.
• Proven ability to thrive in a high-ambiguity environment, demonstrating adaptability and a bias for action.
• Strong systems-thinking mindset, with the ability to balance long-term technical health with short-term business needs.
• Excellent communication skills, with a track record of translating complex technical concepts for diverse stakeholders.