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Staff ML Engineer - GenAI

Uber

Staff ML Engineer - GenAI

Uber

Bangalore, India

·

On-site

·

Full-time

·

1mo ago

Benefits & Perks

Annual team offsites

Remote work flexibility

Health, dental, and vision coverage

Top Tier compensation with equity

Flexible PTO policy

Required Skills

Apache Spark

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

View Company Profile

About the Role

We are looking for a highly motivated GenAI Engineer to join the Customer Obsession team. You will play a critical role in designing conversational GenAI systems and algorithms which would enhance the customer support experience and resolution speed for millions of Uber Eats users worldwide while making O(100s millions) cost savings. You will leverage your expertise in data analysis, machine learning, and engineering to drive insights, identify tech-driven product innovations, optimize algorithms and systems ultimately improving user satisfaction and operational efficiency.

What the Candidate Will Do:

  • Design, develop, and productionize Conversational GenAI solutions in the field of customer support engineering spanning generative AI algorithms, agentic AI design at scale, NLP for query understanding and ranking responses, distillation techniques, etc.
  • Productionize and deploy these models for real-world applications in customer support.
  • Design and analyze experiments using a combination of data analysis/statistical analysis to lead the team to a reasonable inference.
  • Review code and designs of teammates, providing constructive feedback.
  • Collaborate with cross-functional teams to brainstorm new solutions and iterate on the product.
  • Technically lead the team, mentor and guide engineers

What the Candidate Will Need:

  • Experience in building and owning Conversational GenAI models over multiple years, including strong understanding of product and operational metrics and what it takes to improve them.
  • Bachelor's or Master's in Computer Science, Statistics, or a related field or Equivalent Experience in Conversational GenAI
  • Minimum 10+ years of experience in industry with a strong focus on machine learning and optimization.
  • Experience with ML packages such as Tensorflow, Py Torch, JAX, and Scikit-Learn.
  • Solid understanding of statistical analysis and feature engineering techniques.
  • Excellent communication and collaboration skills.
  • Ability to work independently and take ownership of projects.
  • Experience using SQL in a production environment.
  • Experience in experimental design and analysis, exploratory data analysis, and statistical analysis.
  • Experience with dashboarding and using data visualization tools.
  • Experience using statistical methodologies such as sampling, statistical estimates, descriptive statistics, or similar.

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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Client-provided location(s): Bangalore, India

Job ID: Uber-153208

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

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