Skip to main contentA logo with &quat;the muse&quat; in dark blue text.

Senior Machine Learning Engineer

AT Uber
Uber

Senior Machine Learning Engineer

San Francisco, CA

About the Role

The UberEats Feed is the front door to our service. It serves an important role for both users and merchants. For our users, the Feed helps them find a great restaurant or grocery store for their needs. It also serves as an important gateway for them to explore the breadth and depth of UberEats's selection. For merchants, it is the main surface for which they get in front of potential customers to showcase their products. As a Machine Learning Engineer in this role, you will be able to work on various open-ended, challenging, impactful problems.

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

  • Innovate and productionize start-of-the-art recommendation models, and customize for Uber's use cases.
  • Design and build the end-to-end large-scale ML systems to power the HomeFeed Recommendation.
  • Improve the Feed Model ML Quality, Model Serving foundation and the Data foundation.
  • Collaborate with cross-functional and cross-team stakeholders.

Want more jobs like this?

Get jobs delivered to your inbox every week.

Select a location
By signing up, you agree to our Terms of Service & Privacy Policy.

---- Basic Qualifications ----

  • PhD or Master in relevant fields (CS, EE, Math, Stats, etc.) with recommendation system research experiences and 4 years minimum of industry experience with a strong focus on machine learning and recommendation systems.
  • Expertise in deep learning, recommendation systems, or optimization algorithms.
  • Experience with ML frameworks such as PyTorch and TensorFlow.
  • Experience building and productionizing innovative end-to-end Machine Learning systems.
  • Proficiency in one or more coding languages such as Python, Java, Go, or C++.
  • Experience with any of the following: Spark, Hive, Kafka, Cassandra.
  • Strong communication skills and can work effectively with cross-functional partners.

---- Preferred Qualifications ----

  • Publications at industry recognized ML conferences.
  • Experience in simplifying/converting business problems into ML problems.
  • Experience developing complex software systems scaling to millions of users with production quality deployment, monitoring and reliability.

For San Francisco, CA-based roles: The base salary range for this role is USD$185,000 per year - USD$205,500 per year.

For Sunnyvale, CA-based roles: The base salary range for this role is USD$185,000 per year - USD$205,500 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.

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.

Client-provided location(s): San Francisco, CA, USA; Sunnyvale, CA, USA
Job ID: Uber-134684
Employment Type: Full Time

Perks and Benefits

  • Health and Wellness

    • Health Insurance
    • Health Reimbursement Account
    • Dental Insurance
    • Vision Insurance
    • Life Insurance
    • FSA With Employer Contribution
    • Fitness Subsidies
    • On-Site Gym
    • Mental Health Benefits
  • Parental Benefits

    • Fertility Benefits
  • Work Flexibility

    • Flexible Work Hours
    • Remote Work Opportunities
    • Hybrid Work Opportunities
  • Office Life and Perks

    • Casual Dress
    • Pet-friendly Office
    • Snacks
    • Some Meals Provided
    • On-Site Cafeteria
  • Vacation and Time Off

    • Paid Vacation
    • Unlimited Paid Time Off
    • Paid Holidays
    • Personal/Sick Days
    • Sabbatical
    • Volunteer Time Off
  • Financial and Retirement

    • 401(K)
    • Company Equity
    • Performance Bonus
  • Professional Development

    • Work Visa Sponsorship
    • Associate or Rotational Training Program
    • Promote From Within
    • Mentor Program
    • Access to Online Courses
  • Diversity and Inclusion

    • Employee Resource Groups (ERG)
    • Diversity, Equity, and Inclusion Program