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Benefits & Perks
•Annual team offsites
•Flexible PTO policy
•Health, dental, and vision coverage
•Learning and development stipend
•Top Tier compensation with equity
Required Skills
PyTorch
TensorFlow
SQL
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
Uber is launching AV Labs to accelerate the autonomous technology ecosystem. We're building out a high-velocity team of multi-disciplinary experts to turn real-world operations into high-quality data for our autonomous partners. This team will be focused on the hardest problem in AV today: unlocking real-world, long-tail driving data. Autonomy is now a data race-and Uber has an edge: We collect rare, real-world driving data at a scale and capital efficiency no one else can match (millions of Uber trips every hour across cities, conditions, and edge cases create the data autonomy has been missing). We will build platforms that harness scale and real-world complexity to reimagine how the world moves.
You will be an AI/ML engineer in AV Labs and involved in the development and implementation of the latest machine learning techniques for computer vision and perception use cases. The ideal candidate will be able to identify issues, provide solutions and implement the fixes as well as setting a high technical excellence bar in all things we do. You'll be able to collaborate with other engineers across networking, storage, compute, big data and cloud engineering, as well as with partner engineering teams which enables Uber's mission of helping people go anywhere and get anything and earn their way.
What You Will Do
- Design and deliver software and tools as part of our state-of-the-art Machine Learning platform.
- Systems architecture design, including management of upstream and downstream dependencies.
- Provide technical leadership, influence and partner with fellow engineers to architect, design and build scalable solutions for ML technology that can stand the test of scale and availability, while reducing operational overhead.
- Deliver datasets to accelerate ML technologies, sensor data collection, processing, labeling, indexing, etc
- Participate in periodic on-call rotations and be available for critical issues.
- Collaborate with platform, product and security engineering teams, and enable successful use of the latest machine learning techniques.
Basic Qualifications
- Minimum 4 years of working experience in the ML/Robotics industry
- Bachelor degree in computer science, computer engineering or related fields
- Proficient in Python and Linux
- Familiar with OpenCV, Tensor Flow/Py Torch
Preferred Qualifications
- Master or PhD degree in computer vision or robotics
- Familiar with C++
- Familiar with the Robot Operating System (ROS)
Email Address
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- For San Francisco, CA-based roles: The base salary range for this role is USD**$202,000 per year**
- USD**$224,000 per year**.
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
Job ID: Uber-154280
Employment Type: OTHER
Posted: 2026-01-27T19:55:18
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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