By Theofanis Karaletsos, Ersin Yumer, Raquel Urtasun, and Zoubin Ghahramani on behalf of Uber AI Labs and Uber ATG
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. 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 AI Labs or Uber Advanced Technologies Group (ATG).
Artificial intelligence at Uber
Uber’s AI efforts are clustered around two main areas: general AI and applied machine learning through Uber AI, and AI for self-driving cars through Uber ATG.
The Uber AI organization in San Francisco combines efforts from Uber AI Labs in basic research and applications with various platform teams working towards providing and improving services for the rest of the company in fields such as computer vision, conversational AI, and sensing and inference from sensor data. Uber AI Labs is composed of two main wings that feed and reinforce each other: foundational core research and our Connections group, a team focusing on the translation of research into applications for the company in collaboration with platform and product teams.
AI Labs Core
AI Labs Core works on diverse topics ranging the spectrum from probabilistic programming and Bayesian inference to core deep learning research, reinforcement learning, neuroevolution, safety, and artificial intelligence.
AI Labs Connections
AI Labs is working on applied research which can also advance the mission of Uber today. For example, Connections transformed Bayesian optimization from a research field into a service for the company with applications for multiple teams and has deep collaborations with teams working on natural language processing, conversational AI, forecasting, mapping, fraud detection, Uber’s Marketplace, and many other areas.
One of the most ambitious AI applications at Uber is self-driving vehicles. In the context of self-driving technology, 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 these groups, 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., NIPS, 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 (also, see Pyro: Deep Universal Probabilistic Programming), a pioneering effort in systems research combining ideas from Bayesian Inference and deep learning.
The Residency program
Uber AI Residents will be chosen across both AI Labs in San Francisco and ATG in Toronto and San Francisco. Residents will have the opportunity to pursue interests across academic and applied research, meeting both with researchers at AI Labs and ATG, as well as Uber product and engineering teams to converge on initial project directions. Residents will also be encouraged to publish their work externally at top machine learning venues (NIPS, ICLR, ICML, CVPR, EMNLP, ACL, ECCV, ICCV etc.) and through Eng Blog articles, or by releasing open source projects.
Pursuing projects that span disciplines and teams is encouraged. For instance, our 2018 residency class is currently working on foundational research projects in probabilistic modeling, deep learning, 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.
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, including details about the role, required qualifications, and instructions about submitting academic records and any other required documents.
Applications will be considered as early as December 10th, 2018, and are due by Sunday, January 13, 2019 at 11:59 p.m. EST. Additional candidacy communications will be given on a stage-to-stage basis, and finalists are required to have referrals submit two supporting letters for recommendations by February 18, 2019.
Decisions will be sent by March 15th 2019.
Learn more about the Uber AI Residency program and apply today!
Check out research from Uber AI and ATG.