We’re changing the way people think about transportation. Not that long ago we were just an app to request premium black cars in a few metropolitan areas. Now we’re a part of the logistical fabric of more than 600 cities around the world. Whether it’s a ride, a sandwich, or a package, we use technology to give people what they want, when they want it.
For the people who drive with Uber, our app represents a flexible new way to earn money. For cities, we help strengthen local economies, improve access to transportation, and make streets safer.
And that’s just what we’re doing today. We’re thinking about the future, too. With teams working on autonomous trucking and self-driving cars, we’re in for the long haul. We’re reimagining how people and things move from one place to the next.
Uber is a technology company that is changing the way the world thinks about transportation. We are building technology people use everyday. Whether it's heading home from work, getting a meal delivered from a favorite restaurant, or a way to earn extra income, Uber is becoming part of the fabric of daily life.
The Applied Machine Learning team is bringing ML to all parts of the company. As part of the central Machine Learning org, we act as internal consultants who embed with other teams and advance the state of automation and intelligence at Uber. We partner with Data Science and Engineering teams to work on the highest impact projects to ensure we deliver value for Uber and our users. Our team is looking for ML enthusiasts with expertise in NLP, speech, deep learning, and other skills to grow our diversity of skills.
Horserace deep learning architectures (e.g., CNN, LSTM, GRU) to develop the most accurate NLP models for labeling and routing support tickets
Develop computer vision solutions to augment our OCR technology
Prototype real-time updating models for improving the accuracy of our ETAs
Research both supervised and unsupervised methods (e.g., GBTs, 1-class SVM, LSTMs) for detecting fraud
Visualize and simplify Uber’s communication strategy by using topic modeling (e.g., LDA, LSI, & word2vec)
Train deep learning models to replicate the SMS patterns of our driver support agents
MS or PhD in computer science, statistics, or a quantitative domain
3+ years professional experience (post-graduation) delivering, scaling, and managing highly successful and innovative machine learning products
Demonstrable proficiency in coding (Python, Spark, and R preferred) and programming concepts
Know core ML concepts (i.e. feature discovery and engineering, model validation, retraining strategies) like the back of your hand
You bring substantial depth in at least 1-2 ML specialities (i.e. NLP, deep learning, recommender systems) where you can teach/develop others
A commitment to learning - We want someone who seeks to deliver impact, but also invests in themselves and others.
A strong communicator who can partner with others to set a vision and then collaborate to deliver impactful results that are well explained
At Uber we don’t just accept difference—we celebrate it, we support it, and we thrive on it for the benefit of our employees, our products and our community. Uber is proud to be an equal opportunity workplace. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status.