招聘

Staff Machine Learning Engineer, Dynamic Pricing
San Francisco, CA; Sunnyvale, CA
·
On-site
·
Full-time
·
1mo ago
Benefits & Perks
•Wellness benefits
•Top Tier compensation with equity
•Annual team offsites
•Health, dental, and vision coverage
•Flexible PTO policy
Required Skills
Python
TensorFlow
PyTorch
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
About the Role
The mission of the Surge team is to maintain overall marketplace reliability by balancing supply/demand in real-time through dynamic pricing. We build scalable real-time systems to understand the state of the market, forecast future demand, make predictions using ML models, solve network optimization programs, and eventually make pricing decisions for each rider session.
Surge plays a critical role in service of Uber's mission to make transport accessible. We generate billions of dollars in annual gross bookings for the company by optimizing network efficiency and make a significant contribution to driver earnings. In addition to pricing, the signals we generate are some of the most important features used in practically every optimization/ML system across Uber. Although we are a backend team, what we do has an outsized impact on our riders because prices and reliability are two of the most important elements of customer experience.
What You'll Do
You will work with a mixed team of Engineers, Operations Researchers, and Economists to build large-scale pricing optimization systems to set prices based on real-time marketplace conditions for Uber's rides products globally.
- Build and train machine learning models.
- Initiate new areas where machine learning models can make a large impact on the o
Basic Qualifications
- PhD in relevant fields (CS, EE, Math, Stats, etc.) with a focus on Machine Learning.
- 4+ years of experience in an ML role with an emphasis on data and experiment driven model development.
- Expertise in deep learning and optimization algorithms.
- Experience with ML frameworks such as Py Torch and Tensor Flow.
- 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++.
- Strong communication skills and can work effectively with cross-functional partners.
- Strong sense of ownership and tenacity toward hard machine-learning projects.
Preferred Qualifications
-
Experience in serving and monitoring online training systems such as real time recommendation systems.
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Experience designing and implementing novel metrics for performance evaluation.
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Experience handling time series data and time series forecasting (experience handling spatial temporal data is plus).
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Deep understanding of models such as VAE (Variational Auto Encoder), SSM (State space model), and Normalizing Flow.
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Experience in inference optimization and monitoring model performance efficiency and being able to identify bottlenecks.
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Proven track record in conducting experiments and tracking models in high-complexity environments.
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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 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.
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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, Sunnyvale, CA
Job ID: Uber-144034
Employment Type: FULL_TIME
Posted: 2026-01-31T19:57:26
Apply 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
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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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