On the Rides Engineering team, we write code that ignites opportunities for millions of people every day. We're focused on making Uber's core ridesharing products faster, safer, and more reliable by building scalable software solutions for riders and drivers on our platform.
About the Role
Uber is looking for a Senior Engineering Manager to lead a talented team of engineers based in San Francisco and Sunnyvale. As part of the Mobility business at Uber, this role will own, lead, and scale an engineering team focused on the Rider Product Selector.
Rider Product Selector is the surface in Uber Rider App where users get to view and compare available offerings and check out their rides. The Product Selector team focuses on creating an assistive experience using data-driven technologies and machine learning optimizing for multiple business goals (gross bookings, conversion, time to convert, etc). The person who takes this role will need to define the future technology roadmap for Uber's most critical checkout product.
What You'll Do

• Build trust and cultivate a collaborative team culture and help grow the respective leaders in Product Selector focus areas.
• Build a strong engineering brand for Rider Product Selector and be able to attract and retain talent.
• Strategize and influence the product vision, roadmap, and technology platforms in collaboration with the product, business, and infrastructure teams.
• Have an excellent executive presence to communicate the team's vision/plan effectively.
• Translate the strategic roadmap into a practical execution plan with quarterly OKR's.
• Develop impactful machine learning and relevance tech to drive business goals and increase key metrics for the Mobility business and Uber.

Basic Qualifications

• Bachelor's degree or equivalent experience.
• 6+ years proven experience in applied machine learning or AI.
• 3+ years experience of management in building and leading a software engineering team.

Preferred Qualifications

• Master or PhD in Machine Learning or other relevant fields.
• Deep knowledge and experience working in relevance, ML, AI, personalization at a company of scale.
• Proven experience with one or more of: classification, recommendation systems, optimization problems, ranking or similar.
• Strong understanding of technical architecture, system design, and problem solving acuity for sophisticated technical challenges.
• Experience working cross-functionally with Product Management, Data Science, and Business partners.