Sr Engineering Manager: Rider Intelligence

About the Role

As Sr Engineering Manager for the Rider Intelligence team, you will join a team dedicated to using cutting-edge machine learning and AI to create an app experience that feels intuitive and personalized for millions of riders around the world. Your mission will be to ensure that riders always feel understood, with the app effortlessly anticipating their needs-whether they're booking a trip for immediate travel or exploring services that can meet future needs they didn't even know they had.

In this role, you will collaborate closely with product managers, data scientists, and cross-functional teams to design scalable systems that enable a seamless, intelligent rider experience. You'll focus on helping users discover the right products and services tailored to their context, unlocking new possibilities and ensuring Uber is there for them at every step of their journey. This will be powered by building ML models and infrastructure staying at the cutting edge of ML/AI research in the industry.

This is an exciting opportunity to be part of a broader Rider ML team with a far-reaching mission to personalize many aspects of the app and make Uber feel like a personal assistant that's always one step ahead.

\\-\\-\\-\\- What the Candidate Will Do ----

1. Define and execute the Rider ML product and engineering roadmap and strategy, focusing on personalization and discovery experiences that enhance the rider journey.
2. Collaborate with product managers, data scientists, designers, and operations to identify opportunities, prioritize initiatives, and deliver ML-powered features that feel intuitive and assistive.
3. Develop scalable systems that help riders easily book trips when they have an immediate need, while also surfacing personalized recommendations for future planning or unmet needs.
4. Partner with other product & engineering teams to ensure ML frameworks and capabilities are leveraged to create cohesive, delightful user experiences.
5. Stay on top of industry trends and emerging best practices in machine learning and personalization to ensure Uber continues to lead in innovation.

\\-\\-\\-\\- Basic Qualifications ----

1. MS or equivalent experience in Computer Science, Engineering, Mathematics or related field
2. 10+ years of industry experience as an Applied Scientists/Machine Learning Engineer with 5+ years of experience leading team as a manager.
3. Experience in exploratory data analysis, statistical modeling, hypothesis testing, and experimental design.
4. Experience working with cross-functional teams(product, science, product ops etc).

\\-\\-\\-\\- Preferred Qualifications ----

1. Experience leading team of teams through other managers.
2. PhD in Machine Learning, Data Science or related fields.
3. Demonstrated ability to align technical investments with high-impact use cases and broader business objectives.
4. Experience crafting an ML-first vision, identifying machine learning needs across multiple products, and proposing solutions that serve long-term user and business needs.
5. Experience in consumer-facing products, with a focus on personalization, content recommendation, and understanding user context to create tailored experiences.
6. Extensive experience in data analysis and experimentation, with the ability to craft and execute multivariate tests to inform product direction.
7. Proven ability to navigate a diverse set of opinions among cross-functional teams, synthesize different perspectives, and drive decisions effectively.
8. Strong communication skills, with the ability to articulate complex ideas clearly to both technical and non-technical audiences.

Uber's mission is to reimagine the way the world moves for the better. Here, bold ideas create real-world impact, challenges drive growth, and speed fuels progress. What moves us, moves the world - let's move it forward, together.

Uber is proud to be an Equal Opportunity 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](;br>
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 Sunnyvale, CA-based roles: The base salary range for this role is USD$267,000 per year - USD$297,000 per year.

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 [](;br>
Uber's mission is to reimagine the way the world moves for the better. Here, bold ideas create real-world impact, challenges drive growth, and speed fuels progress. What moves us, moves the world - let's move it forward, together.

Uber is proud to be an Equal Opportunity 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](;br>
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.