Uber AI Labs and Uber ATG Toronto are excited to announce the Uber AI Residency, an intensive one-year research training program slated to begin this summer.  

Uber has invested substantially in machine learning and artificial intelligence, with groups around the company working on a variety of techniques—deep learning, reinforcement learning, neuroevolution, probabilistic modeling,  natural language processing, computer vision, and self-driving cars to name just a few—to enable a set of real world applications just as varied. When machine learning works well, Uber can provide improved user experiences across our services. Among other applications, we apply these technologies to developing:

  • Better prediction of spatiotemporal rider demand patterns across a city enables both shorter wait times for riders and shorter gaps between trips for driver-partners, leading to higher average hourly earnings.
  • Models enabling more intelligent fusion of mapping, traffic, and GPS data facilitate more efficient route selection and more precise pick-up and drop-off locations, leading to smoother, more enjoyable trips.
  • Natural language understanding, permitting faster perception and resolution of customer support tickets, for example, enabling a rider to recover the backpack that they left behind on a trip more quickly.
  • Perception, prediction, motion planning, control, localization, and mapping for self-driving vehicles.

At Uber’s scale, these advances or those in directions yet to be explored have the potential to positively impact millions of people.

Machine learning has grown by leaps and bounds over the last decade, vaulting from academic curio to a real-world workhorse powering a vast number of business applications. However, there remains much important (and fun!) science and engineering to be done. Taking inspiration from similar programs, Uber AI Labs and Uber ATG Toronto created the Uber AI Residency to allow up-and-coming researchers accelerate their careers in machine learning and AI research and practice.

Residents will have the flexibility to pursue a range of different directions in research and application with both Uber AI Labs and Uber ATG Toronto. Some projects might involve fundamental AI research, pushing the frontiers of the field by developing new algorithms for learning and control, while others might include devising and training new models to help more efficiently transport people and things in the physical domain, improving real world user experiences. Still other projects might use new or existing models in concert with anonymized data sets to enable understanding of societal conditions, for example, by looking at the wage gap anchored by data. To effectively accomplish research goals drawn from this diverse set of possibilities, residents will have the opportunity to work directly with researchers and engineers at Uber AI Labs, Uber ATG Toronto, and across the entire company.

The Uber AI Residency will last for 12 months, kicking off with an initial period of learning, exploration, and collaborative ideation. During this period, residents will meet with researchers at AI Labs and Uber ATG Toronto, as well as product and engineering teams to converge on initial project directions. Residents will be paired with mentors from Uber AI Labs or Uber ATG Toronto, as well as relevant research teams, to support them throughout their fellowship.  Pursuing projects that span disciplines and teams is encouraged. Residents will be also be encouraged to publish their work externally at top machine learning venues (NIPS, ICLR, ICML, CVPR, EMNLP, ACL, ECCV, ICCV etc.), via blog posts, or by publishing open source projects.

Residents will be embedded directly with Uber AI Labs at our San Francisco headquarters and/or Uber ATG at our Toronto office, and candidates of all academic and geographic backgrounds are encouraged to apply. Applicants who require a work visa will be assessed on a case-by-case basis for those who are accepted.

Sound like fun? Apply by March 18, 2018.

Editor’s Note March 1, 2018: We have updated this article to reflect the inclusion of Uber ATG Toronto as a co-sponsor of this residency. — Molly Vorwerck

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Jason Yosinski
Jason Yosinski is a Machine Learning Researcher at Uber AI Labs.
Zoubin Ghahramani
Zoubin Ghahramani is Uber’s Chief Scientist.
Raquel Urtasun
Head of Uber ATG Toronto in Uber ATG
Raquel Urtasun is the Head of Uber ATG Toronto, as well as an Associate Professor in the Department of Computer Science at the University of Toronto and a co-founder of the Vector Institute for AI.