About the Role
Whether engineering a more efficient query understanding or providing riders personalized ranking results, our search technologies are integral to the magic of the Uber platform. On the Maps Engineering team, we use the latest ML, NLP, and neural network solutions to help users find the intended locations online more intelligently and efficiently.
We are a 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 lead 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 user-facing products with global impact. This is your chance to develop cutting-edge technology that will touch every Uber trip!
What the Candidate Will Need / Bonus Points
---- What the Candidate Will Do ----

• Provide technical leadership, and drive technical direction for the search platform
• Partner with other engineering teams, product owners, data scientists and stakeholders to build solutions
• Build ML models and search backend services
• Lead one of the search teams of 4-5 engineers

---- Basic Qualifications ----

• PhD or equivalent in Computer Science, Engineering, Mathematics or related field AND 2-years full-time Software Engineering work experience OR 5-years full-time Software Engineering work experience, WHICH INCLUDES 3-years total technical software engineering experience in one or more of the following areas:
• Programming language (e.g. C, C++, Java, Python, or Go)
• Large-scale 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 3-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.

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.
Offices continue to be central to collaboration and Uber's cultural identity. Unless formally approved to work fully remotely, Uber expects employees to spend at least half of their work time in their assigned office. For certain roles, such as those based at green-light hubs, employees are expected to be in-office for 100% of their time. Please speak with your recruiter to better understand in-office expectations for this role.
For San Francisco, CA-based roles: The base salary range for this role is $207,000 per year - $230,000 per year. For Sunnyvale, CA-based roles: The base salary range for this role is $207,000 per year - $230,000 per year. For all US locations, you will be eligible to participate in Uber's bonus program, and may be offered an equity award & other types of comp. You will also be eligible for various benefits. More details can be found at the following link https://www.uber.com/careers/benefits.