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Senior Machine Learning Engineer, Product Platform & Data Eng

Uber

Senior Machine Learning Engineer, Product Platform & Data Eng

Uber

Bangalore, India

·

On-site

·

Full-time

·

5d ago

Your Role & Mission:

Applied AI is a horizontal AI team at Uber collaborating with business units across the company to deliver cutting-edge AI solutions for core business problems. We work closely with engineering, product and data science teams to understand key business problems and the potential for AI solutions, then deliver those AI solutions end-to-end. Key areas of expertise include Generative AI, Computer Vision, and Personalization.

We are looking for a strong Senior ML engineer to be a part of a high-impact team at the intersection of classical machine learning, generative AI, and ML infrastructure. In this role, you'll be responsible for delivering Uber's next wave of intelligent experiences by building ML solutions that power core user and business-facing products.

What You'll Be Working On:

  1. Build ML solutions to solve business needs across the Rider organization with over 300+ engineers. Some of the types of projects you will work on for e.g:
  • Address the under-supply problem and reduce the pickup ETA
  • Improve the overall experience of the Riders at the Reserve
  • Provide effective ETR for Drivers when they take Intercity trips

Required Qualifications:

  1. Master or PhD or equivalent experience in Computer Science, Engineering, Mathematics or a related field and 2 years of Software Engineering work experience, or 5 years Software Engineering work experience.
  2. Experience in programming with a language such as Python, C, C++, Java, or Go.
  3. Experience with ML packages such as Tensorflow, Py Torch, JAX, and Scikit-Learn.
  4. Experience with SQL and database systems such as Hive, Kafka, and Cassandra.
  5. Experience in the development, training, productionization and monitoring of ML solutions at scale.
  6. Strong desire for continuous learning and professional growth, coupled with a commitment to developing best-in-class systems.
  7. Excellent problem-solving and analytical abilities.
  8. Proven ability to collaborate effectively as a team player

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 fuelds progress. What moves us, moves the world - let's move it forward, together.

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.

Accommodations may be available based on religious and/or medical conditions, or as required by applicable law. To request an accommodation, please reach out to accommodations@uber.com.

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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