refresh

트렌딩 기업

트렌딩

채용

JobsUber

Staff Machine Learning Engineer - Marketplace Pricing

Uber

Staff Machine Learning Engineer - Marketplace Pricing

Uber

New York, NY; San Francisco, CA; Seattle, WA; Sunnyvale, CA

·

On-site

·

Full-time

·

1mo ago

Benefits & Perks

Remote work flexibility

Parental leave program

Learning and development stipend

Flexible PTO policy

Health, dental, and vision coverage

Required Skills

SQL

Apache Spark

Airflow

  • Jobs

  • View All Jobs

  • Companies

  • Advice

  • Coaching

  • Newsletter

  • Employers

  • Sign In

  • Saved Companies

  • Account Settings

  • Sign Out

Uber

Staff Machine Learning Engineer

  • Marketplace Pricing

3+ months ago• Seattle, WA (+3 more)San Francisco, CANew York, NYSunnyvale, CA
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:

Uber's Marketplace is at the heart of Uber's business and the Dynamic Supply Pricing (DSP) team develops the models, algorithms, signals, and large-scale distributed systems that power real-time driver pricing for billions of rides. Engineers on the team work on cutting-edge marketplace ML problems and real-time multi-objective optimizations serving 1M+ predictions/second. They regularly present $1B+ opportunities to executive stakeholders and receive close mentorship from the most senior engineers within the organization, setting you up for fast-tracked career growth and the opportunity to learn from experienced technical leaders.

We are looking for exceptional ML engineers with a track record of extraordinary impact and with a passion for building large-scale systems that optimize multi-sided real-time marketplaces. In this role, you will lead the design, development, and productionization of advanced ML models and pricing algorithms, covering deep learning, causal modeling, and reinforcement learning. You will work with engineers, product managers, and scientists to set the team's technical direction and solve some of Uber's most challenging and most complex business problems in order to provide earnings opportunities for millions of drivers worldwide.

Want more jobs like this?

Get jobs in Seattle, WA 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 You Will Do

  • Drive technical strategy and roadmap ownership over a 1+ year horizon and own the implementation, including platform-level architecture decisions, executive communication and alignment, technical mentorship, and cross-team technical influence
  • Lead the design, development, and productionization of end-to-end ML solutions for large-scale distributed systems serving billions of trips
  • Develop novel pricing approaches for online marketplaces combining machine learning, algorithmic game theory, and optimization to provide earnings opportunities for millions of drivers
  • Work with a team of engineers, product managers, and scientists to design and deliver high-impact technical solutions to complex business problems

Basic Qualifications:

  • Ph.D., M.S. or Bachelor's degree in Computer Science, Machine Learning, or Operations Research, or equivalent technical background with exceptional demonstrated impact
  • 6+ years experience leading the development and deployment of ML models and optimization algorithms in large-scale production environments at top-tier ML companies (e.g. 1M+ predictions/sec or 100M+ users). Track record of delivering outstanding business impact over multiple quarters
  • Proficiency in programming languages such as Python, Scala, Java, or Go
  • Proficiency with large-scale data systems (e.g. Spark, Ray), real-time processing (e.g. Flink), and microservices architectures
  • Proficiency in the development, training, productionization and monitoring of ML solutions at scale, ranging from offline pipelines to online serving and MLOps
  • Experience in developing and deploying pricing algorithms for multi-sided real-time marketplaces with strategic agent behavior
  • Deep understanding of modern ML algorithms (e.g. DNNs, multi-task models, transformers) and mathematical optimization (e.g. multi-objective, LP, convex optimization)

Preferred Qualifications:

  • Experience developing multi-year technical strategies and cross-team platform architecture, and proficiency owning technical roadmap and leading complex technical projects while substantially influencing the scope and output of others

  • Track record of translating complex business problems into technical solutions and driving multi-functional projects across multiple teams

  • Excellent communication skills to lead initiatives across multiple product areas and collaborate effectively with cross-functional teams

  • Proficiency in reinforcement learning and causal machine learning

  • For New York, NY-based roles: The base salary range for this role is USD**$232,000 per year**

  • USD**$258,000 per year**.

  • For San Francisco, CA-based roles: The base salary range for this role is USD**$232,000 per year**

  • USD**$258,000 per year**.

  • For Seattle, WA-based roles: The base salary range for this role is USD**$232,000 per year**

  • USD**$258,000 per year**.

  • For Sunnyvale, CA-based roles: The base salary range for this role is USD**$232,000 per year**

  • USD**$258,000 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): Seattle, WA, San Francisco, CA, New York, NY, Sunnyvale, CAJob ID: Uber-146337Employment Type: FULL_TIMEPosted: 2025-07-19T00:28:49Apply 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

Staff Machine Learning Engineer Apple Cupertino, CAStaff Machine Learning Engineer Liftoff Reedley, CAStaff Machine Learning Engineer Uber Amsterdam, Netherlands

Suggested Searches

senior jobs Uber jobs All jobs

Search Additional Jobs

Staff Machine Learning Engineer Jobs in Seattle, WAStaff Machine Learning Engineer Jobs in San Francisco, CAStaff Machine Learning Engineer Jobs in New York, NYJobs in Seattle, WAJobs 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