refresh

トレンド企業

Trending

採用

JobsUber

Senior Machine Learning Engineer - Ads

Uber

Senior Machine Learning Engineer - Ads

Uber

New York, NY; San Francisco, CA

·

On-site

·

Full-time

·

1mo ago

Benefits & Perks

Flexible PTO policy

Learning and development stipend

Health, dental, and vision coverage

Annual team offsites

Remote work flexibility

Required Skills

Apache Spark

SQL

PyTorch

  • Jobs

  • View All Jobs

  • Companies

  • Advice

  • Coaching

  • Newsletter

  • Employers

  • Sign In

  • Saved Companies

  • Account Settings

  • Sign Out

Uber

Senior Machine Learning Engineer

  • Ads

1 week ago• San Francisco, CA (+1 more)New York, NY
Viewed on February 1, 2026
Apply on company site

About Us

Uber is changing how people think about transportation, part of the logistical fabric of 600+ cities - giving people what they want when they want it.

  • Size: 10000+ employees
  • Industry: Technology

View Company Profile:

About the Role:

The Ads Machine Learning (Ads ML) team at Uber is responsible for providing relevant ad recommendations to the users across the different applications within the Uber ecosystem. We focus on building a deep understanding of both user and merchant behavior to generate accurate ML signals that enhance the Ads auction system providing accurate pricing for our advertisers. Our goal is to maximize the benefits for both users and merchants within Uber's Ads distribution system.

You will directly impact Uber's Ads systems by defining and executing the Ads ML roadmap, with a focus on enabling and accelerating large-scale improvements to our recommendation and auction systems. Developing relevant, robust, and observable ad recommendations is crucial to Uber's fast growing Ads Business strategy, making this a highly impactful role.

Want more jobs like this?

Get jobs in San Francisco, CA delivered to your inbox every week.
Email Address

Send me The Muse newsletters for the best in career advice and job search tips.

Get jobs!
By signing up, you agree to our ---- What the Candidate Will Do ----

  • Design and implement machine learning models and algorithms to optimize ad recommendations and auction mechanisms.
  • Develop and maintain scalable ML pipelines and data infrastructure to support real-time and batch processing of large-scale datasets.
  • Apply advanced statistical and machine learning techniques to generate insights and improve the effectiveness of ad targeting and delivery.
  • Collaborate with data scientists and engineers to build and refine predictive models that enhance user engagement and merchant benefits.
  • Conduct rigorous experimentation and A/B testing to validate model performance and iterate on improvements.
  • Define success metrics and develop dashboards to monitor and visualize the performance of ML models in production.
  • Work closely with cross-functional teams, including Product, Engineering, and Data Science, to translate business requirements into ML solutions.
  • Mentor and provide technical guidance to junior ML engineers and data scientists.
  • Stay up-to-date with the latest research and advancements in machine learning, recommendation systems, and ad auction techniques.

---- Basic Qualifications ----

  • Bachelor's degree or equivalent experience in Computer Science, Computer Engineering, Data Science, ML, Statistics, or other quantitative fields.
  • Proven experience with designing and implementing machine learning models in production environments.
  • Proficiency in using Python for developing ML models and handling large-scale data sets.
  • Solid understanding of SQL and experience using it in a production environment.
  • Strong grasp of Big Data architecture and experience with ETL frameworks and platforms.
  • Hands-on experience with building batch data pipelines using technologies like Spark or other map-reduce frameworks.
  • Expertise in experimental design and analysis, including A/B testing, exploratory data analysis, and statistical analysis.
  • Experience with data visualization tools and creating insightful dashboards.
  • Proficiency with methodologies such as sampling, statistical estimates, and descriptive statistics.
  • Ability to synthesize complex data analyses into clear and actionable insights to influence product direction.
  • Experience with recommendation systems.
  • Fast learner with a passion for solving complex problems and asking thoughtful questions to ensure effective solutions.
  • Strong communication skills to engage with technical, non-technical, and executive audiences effectively.
  • Commitment to seeking and providing timely feedback to drive continuous improvement.

---- Preferred Qualifications ----

  • 5 years of industry experience as an ML engineer or equivalent.

  • Expertise in building sophisticated systems and knowledge of Hadoop-related technologies such as HDFS, Kafka, Hive, and Presto.

  • Experience managing projects across large, ambiguous scopes and driving initiatives in a fast-moving, cross-functional environment.

  • Experience with enabling production-scale and maintaining large ML models.

  • Experience in one or more object-oriented programming languages (e.g. Python, Go, Java, C++).

  • Experience with REST APIs and Distributed Messaging / Kafka.

  • Familiarity with recommendation systems and modern ad auction techniques.

  • Experience with ad auctioning systems.

  • Experience with state-of-the-art deep learning techniques.

  • Advanced degree (Ph.D. or M.S.) in Data Science, ML, or related disciplines.

  • For New York, NY-based roles: The base salary range for this role is USD**$202,000 per year**

  • USD**$224,000 per year**.

  • For San Francisco, CA-based roles: The base salary range for this role is USD**$202,000 per year**

  • USD**$224,000 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.

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.

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, New York, NYJob ID: Uber-152623Employment Type: FULL_TIMEPosted: 2026-01-21T19:59:22Apply on company site

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

Apply on company site

Similar Jobs

Senior Machine Learning Engineer Atlassian Austin, TXSenior Machine Learning Engineer Atlassian Bangalore, India Senior Machine Learning Engineer Atlassian San Francisco, CA

Suggested Searches

senior jobs Uber jobs All jobs

Search Additional Jobs

Senior Machine Learning Engineer Jobs in San Francisco, CASenior Machine Learning Engineer Jobs in New York, NYJobs in San Francisco, CAJobs in New York, NYThe Muse LogoA logo with "the muse" in white text.

of Use

  • Popular Jobs

  • New York Jobs

  • San Francisco Jobs

  • Seattle Jobs

  • Engineering Jobs

  • Marketing Jobs

  • Information Technology Jobs

  • Salaries

Get Involved

  • For Employers
  • The Muse Book: The New Rules of Work
  • For Career Coaches
  • Tell A Friend

Join The Conversation:

  • Facebook

  • LinkedIn

  • Twitter

  • Pinterest

  • Instagram

Total Views

0

Apply Clicks

0

Mock Applicants

0

Scraps

0

About Uber

Uber

Uber develops, markets, and operates a ride-sharing mobile application that allows consumers to submit a trip request.

10,001+

Employees

San Francisco

Headquarters

$120B

Valuation

Reviews

3.1

10 reviews

Work Life Balance

4.2

Compensation

2.3

Culture

3.5

Career

2.0

Management

2.5

45%

Recommend to a Friend

Pros

Flexible hours and schedule

Meeting different people and cultures

Make your own hours

Cons

Inconsistent and low pay

Safety concerns with passengers

Traffic and difficult drivers

Salary Ranges

23,534 data points

Junior/L3

Mid/L4

Senior/L5

Staff/L6

Junior/L3 · Data Scientist L3

0 reports

$145,456

total / year

Base

-

Stock

-

Bonus

-

$123,638

$167,274

Interview Experience

5 interviews

Difficulty

3.0

/ 5

Duration

14-28 weeks

Offer Rate

40%

Experience

Positive 80%

Neutral 20%

Negative 0%

Interview Process

1

Application Review

2

Online Assessment

3

Recruiter Screen

4

Technical Phone Screen

5

Case Study/Analytics Test

6

Final Loop/Panel Interview

7

Offer

Common Questions

Coding/Algorithm

System Design

Behavioral/STAR

Case Study

Technical Knowledge