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Machine Learning Engineering II - PhD Computer Vision Research

Uber

Machine Learning Engineering II - PhD Computer Vision Research

Uber

Sunnyvale, CA

·

On-site

·

Full-time

·

1mo ago

Compensation

$171,000 - $171,000

Benefits & Perks

Health, dental, and vision coverage

Top Tier compensation with equity

Annual team offsites

Learning and development stipend

Required Skills

SQL

PyTorch

Apache Spark

About the Role

You will be an ML engineer doing Autonomous Vehicles related research. An ideal candidate will drive foundational and applied research that advances the capabilities of next-generation autonomous systems.

What the Candidate Will Need / Bonus Points

---- What the Candidate Will Do ----

  1. Work on cutting edge research problems in the Autonomous Vehicles domain.
  2. Publish papers in ML conferences.
  3. Collaborate with the engineering team to productionize research ideas.

---- Basic Qualifications ----

  • Ph.D., M.S. or Bachelor's degree in Computer Vision, Computer Science, Machine Learning, or equivalent technical background with exceptional demonstrated impact
  • 2+ years of experience in developing and deploying machine learning models
  • Proficiency in programming languages such as Python, Scala, Java, or Go
  • Publications in top ML conferences.
  • Deep understanding in computer vision and large language models.
  • Proficient in prototyping research ideas using popular deep learning frameworks.

---- Preferred Qualifications ----

  1. Experience with Autonomous Vehicles related research.
  • For Sunnyvale, CA-based roles: The base salary range for this role is USD**$171,000 per year**
  • USD**$190,000 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.

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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