Job Description

About the Role

Maps is foundational to every Uber experiencewhether for riders, eaters, or earners. From pickup and dropoff location search, to rendezvous point recommendations, to optimal route and ETA predictionsMaps services power the entire lifecycle of a Ride or Delivery.

As a Machine Learning Engineer on the Uber Maps team, you will play a key role in developing intelligent systems that drive Ubers Location and Mapping capabilities across Rides, Eats, and other lines of business.

In this highly impactful role, you will own the end-to-end ML lifecycle: from feature engineering and model development to experimentation, deployment, monitoring, explainability, and ongoing maintenance. Youll also contribute to the design of backend platforms that serve ML predictions at scale in real-time. This is a unique opportunity to collaborate with a world-class team of applied scientists, engineers, and product managersdelivering tangible impact on millions of users. If you have a growth mindset and a passion for solving complex problems at scale, this is the role for you.

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

1. Build next-generation ML models using advanced ML tools like pytorch, tensorflow, MLLib on Uber's Machine Learning Platform.
2. Own the entire modeling lifecycle end-to-end including feature creation, model development and testing, experimentation, monitoring and explainability, and model maintenance.
3. Develop and maintain Go/Java based backend platforms that integrate with various critical business workflows at Uber to provide predictions at scale.
4. Participate & drive team's operational processes: regular service and model deployments, observability and system robustness improvements and oncall shifts.
5. Collaborate with applied scientists, engineers & product managers to drive solutions for open-ended business problems.

---- Basic Qualifications ----

1. 5+ years of industry experience (or 1+ year industry experience post PhD) of developing advanced machine learning models with business impact.
2. Experience shipping production-grade ML models and optimization systems, and designing sophisticated experimentation techniques.
3. Hands-on experience in building and maintaining scalable backend systems and pipelines to serve model predictions.

---- Preferred Qualifications ----

1. M.S., or PhD. in Computer Science, Statistics, or other related quantitative fields.
2. Deep domain knowledge in Maps data & tech.

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 Ubers 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 USD$223,000 per year - USD$248,000 per year.

For Sunnyvale, CA-based roles: The base salary range for this role is USD$223,000 per year - USD$248,000 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 .

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 Ubers 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.

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