Announcing the 2020 Uber AI Residency

Connecting the digital and physical worlds safely and reliably on the Uber platform presents exciting technological challenges and opportunities. For Uber, artificial intelligence (AI) is essential to developing systems that are capable of optimized, automated decision making at scale.

AI at Uber is a rapidly growing area across both research and applications, including self-driving vehicles. On behalf of Uber, we invite you to join us on our journey as an Uber AI Resident.

Established in 2018, the Uber AI Residency is a 12-month training program for recent college and master’s graduates, professionals who are looking to reinforce their AI skills, and those with quantitative skills and interest in becoming an AI researcher at Uber.

Artificial intelligence at Uber

Uber’s AI efforts are clustered around two main areas: general AI and applied machine learning to solve Uber’s challenging problems in ride sharing, Uber Eats delivery, and self-driving vehicles, among others. This year’s AI residency program will focus on our self-driving cars project through Uber Advanced Technology Group (ATG). 

Uber ATG

One of the most ambitious AI applications at Uber is self-driving vehicles. In the context of self-driving, AI enables our systems to perceive the surrounding environment using  multiple sensors, predict the motion and intent of actors in the near future, and plan safe maneuvers for the self-driving vehicle. Creating high definition maps and localizing self-driving vehicles with the precision of a few centimeters are also important components of these technologies that provide critical data about the vehicle’s environment. 

Furthermore, learning what and how to simulate is a focus of interest for our researchers at ATG. As all the modules mentioned above are powered by AI, topics related to generative models, reinforcement learning, imitation learning, deep structured models, network architectural search, model compression, learning in the presence of noisy and unstructured data, and other exciting research areas are very actively pursued by our team. 

ATG R&D Labs

Uber ATG R&D Labs, spanning our Toronto and San Francisco offices, are potential locations for the Uber AI Residency program, providing a unique opportunity to work with distinguished researchers to develop advanced machine learning and computer vision techniques for solving one of the most challenging problems of the century. 

Open source & publication opportunities

Across Uber, we are committed to an open and inclusive research mission that benefits the community at large through both Uber AI and Uber ATG Research. We actively publish papers across our interest domains in top conferences (e.g., NeurIPS, ICLR, ICML, CVPR, EMNLP, ACL, ECCV, ICCV, IROS, ICRA, CoRL). We are also active in giving back to the machine learning community through high profile open source projects such as the Pyro probabilistic programming language, a pioneering effort in systems research combining ideas from Bayesian Inference and deep learning, and Ludwig, a code-free deep learning toolbox.

The Residency program

Uber AI Residents will be chosen across San Francisco and Toronto locations. Residents will have the opportunity to pursue interests across academic and applied research, meeting both with researchers, as well as Uber product and engineering teams to converge on initial project directions. Residents are often able to share  their work with the broader community through public presentations, blog posts, or open source releases. 

Pursuing projects that span disciplines and teams is encouraged. For instance, our 2019 residency class is currently working on foundational research projects in probabilistic modeling, deep learning, and reinforcement learning, as well as computer vision. They have multiple results submitted to top scientific venues, and their contributions also directly impact Uber’s business in partnership with Uber’s technology teams.

Apply today

Applications are open now! We encourage applying well in advance, as applications are evaluated on a rolling basis. 

Applicants can find additional information about the residency on our website. Details about the role, required qualifications, and instructions about submitting academic records and any other required documents can be found on the application page.

Applications will be considered as early as January 6, 2020, and are due by Sunday, January 19, 2020 at 11:59 p.m. EST. Additional candidacy communications will be given on a stage-to-stage basis. Finalists who make it to the final rounds of interviews are required to have referrals submit a letter of recommendation by February 21, 2020 at 11:59 p.m. EST. 

Decisions will be shared with applications in mid-March, 2020. 

Learn more about the Uber AI Residency program and apply today

Check out our research publications, and get to know the self-driving research team.

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Ersin Yumer
Ersin Yumer is a Staff Research Scientist, leading the San Francisco research team within Uber ATG R&D. Prior to joining Uber, he led the perception machine learning team at Argo AI, and before that he spent three years at Adobe Research. He completed his PhD studies at Carnegie Mellon University, during which he spent several summers at Google Research as well. His current research interests lie at the intersection of machine learning, 3D computer vision, and graphics. He develops end-to-end learning systems and holistic machine learning applications that bring signals of the visual world together: images, point clouds, videos, 3D shapes and depth scans.
Zoubin Ghahramani
Zoubin Ghahramani is Chief Scientist of Uber and a world leader in the field of machine learning, significantly advancing the state-of-the-art in algorithms that can learn from data. He is known in particular for fundamental contributions to probabilistic modeling and Bayesian approaches to machine learning systems and AI. Zoubin also maintains his roles as Professor of Information Engineering at the University of Cambridge and Deputy Director of the Leverhulme Centre for the Future of Intelligence. He was one of the founding directors of the Alan Turing Institute (the UK's national institute for Data Science and AI), and is a Fellow of St John's College Cambridge and of the Royal Society.
Raquel Urtasun
Raquel Urtasun is the Chief Scientist for Uber ATG and the Head of Uber ATG Toronto. She is also a Professor at the University of Toronto, a Canada Research Chair in Machine Learning and Computer Vision and a co-founder of the Vector Institute for AI. She is a recipient of an NSERC EWR Steacie Award, an NVIDIA Pioneers of AI Award, a Ministry of Education and Innovation Early Researcher Award, three Google Faculty Research Awards, an Amazon Faculty Research Award, a Connaught New Researcher Award, a Fallona Family Research Award and two Best Paper Runner up Prize awarded CVPR in 2013 and 2017. She was also named Chatelaine 2018 Woman of the year, and 2018 Toronto’s top influencers by Adweek magazine