Job Description
About the Role
Uber Engineering is growing quickly as we look to take on exciting opportunities at scale around the world.
The Repair Engine team is building a centralized platform and ecosystem at Uber aimed at significantly improving service reliability by Detecting, Diagnosing, and Repairing production incidents for both infrastructure and product services. Our mission is to minimize Mean Time To Detect (MTTD) and Minimize Mean Time To Mitigate (MTTM), stopping Bad releases before it happens, ultimately preventing impactful production incidents and outages across Uber. There are multiple opportunities in exploring research related to the application of Machine Learning to advance the Recall and Precision of the system.
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We want to explore the use of causal inference methods to determine the underlying causes of system issues. This may involve investigating observational causal discovery, intervention recognition, and the application of LLMs with code knowledge. Graph-based approaches and the integration of anomaly detection, root cause analysis, and explainable AI are potential research directions. This will enhance the understanding of system behavior and the development of automated, targeted solutions. Also, we want to build reinforcement learning agents for the automation of mitigation strategies. This includes exploring multi-objective RL, state representation, action space design, and the use of simulation environments for training which would positively impact our mitigation effectiveness.
We are looking for a candidate with strong theoretical understanding of and practical experience with machine learning, particularly in one or more of the following areas: causal inference, reinforcement learning, deep learning, probabilistic graphical models.
What You'll Do
- Drive exciting, ambitious, previously unsolved projects from end to end.
- Thrive in ambiguous product requirements.
- Iterate fast to explore possible solutions.
- Make data-driven decisions with exceptional execution.
- Collaborate closely with product managers and data scientists.
- Be motivated to own projects and push them forward with independence.
- Most importantly, have a passion for making Uber better for our customers.
- Publish your work at top computer science conferences.
Basic Qualifications
- Ongoing PhD in Computer Science, Machine Learning, Artificial Intelligence or related field.
- Prior experience with relevant machine learning libraries and frameworks (e.g., TensorFlow, PyTorch, scikit-learn).
- Solid analytical and problem-solving skills.
- Excellent coding skills and software design skills.
- Available for a 3 month full time internship from July until September or October until December 2025.
- Work authorization in the Netherlands
Preferred Qualifications
- Ability to communicate effectively with both technical and business partners.
- Experience in simplifying/converting business problems into technical problems.
- Research mentality with a bias towards action to structure a project from idea to experimentation to prototype to implementation.
- Experience presenting at industry-recognized academic conferences.
- Published papers in Artificial Intelligence.
At Uber, we ignite opportunity by setting the world in motion. We take on big problems to help drivers, riders, delivery partners, and eaters get moving in more than 10,000 cities around the world.
We welcome people from all backgrounds who seek the opportunity to help build a future where everyone and everything can move independently. If you have the curiosity, passion, and collaborative spirit, work with us, and let's move the world forward together.
Uber is proud to be an Equal Opportunity/Affirmative Action 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.