About the role:
Partners with stakeholders to design, develop, optimize, and productionize machine learning (ML) or ML-based solutions and systems that are used within a team to solve complex problems with multiple dependencies. This role also leads team efforts to leverage and improve ML infrastructure for model development, training, deployment needs and scaling ML systems.
About the Team:
Whether engineering more accurate ETAs or helping drivers navigate to the perfect pick-up spot, our mapping technologies are integral to the magic of the Uber platform. On the Maps Engineering team, we use the latest ML, GPS, and telematics solutions to make transportation on our platform safer and more accessible.
We are a very small team of engineers responsible for determining a convenient origin and destination of all trips worldwide. We own the search platform and backend services that power the pickup and dropoff experiences for all Uber jobs - be it Rides, Eats, or Freight! As a machine learning engineer on this team you would help us build out the ML models that drive everything from ETA calculations to determining the optimal pickup and drop off for riders and couriers globally. You will be working with some of the world's most experienced mapping professionals, data scientists, software engineers, and research scientists on a user-facing products with global impact. This is your chance to develop cutting-edge technology that will touch every Uber trip!
- PhD or equivalent in Computer Science, Engineering, Mathematics or related field OR 3-years full-time Software Engineering work experience, WHICH INCLUDES 2-years total technical software engineering experience in one or more of the following areas:
- Programming language (e.g. C, C++, Java, Python, or Go)
- Training using data structures and algorithms
- Modern machine learning algorithms (e.g., tree-based techniques, supervised, deep, or probabilistic learning)
- Machine Learning Software such as Tensorflow/Pytorch, Caffe, Scikit-Learn, or Spark MLLib
- Note the 2-years total of specialized software engineering experience may have been gained through education and full-time work experience, additional training, coursework, research, or similar (OR some combination of these). The years of specialized experience are not necessarily in addition to the years of Education & full-time work experience indicated.
- Scalable ML architecture
- Feature management
- Deep Learning
- At least five (5) years of software engineering experience and building production scale ML models
- Experience shipping high-quality features on schedule
- Experience building large scale distributed systems
- Experience implementing projects with multiple dependencies
- Detailed problem-solving approach and knowledge of algorithms, data structures, and complexity analysis
At Uber, we reimagine the way the world moves for the better. The idea was born on a snowy night in Paris in 2008, and ever since then, our DNA of reimagination and reinvention carries on. We've grown into a global platform moving people and things in ever-expanding ways, taking on big problems to help drivers, riders, delivery partners, and eaters make movement happen at the push of a button for everyone, everywhere.
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.