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Staff Machine Learning Engineer - Marketplace Pricing
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
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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.
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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
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Track record of translating complex business problems into technical solutions and driving multi-functional projects across multiple teams
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Excellent communication skills to lead initiatives across multiple product areas and collaborate effectively with cross-functional teams
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Proficiency in reinforcement learning and causal machine learning
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For New York, NY-based roles: The base salary range for this role is USD**$232,000 per year**
-
USD**$258,000 per year**.
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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
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About Uber
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
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