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Senior Machine Learning Engineer

AT Uber
Uber

Senior Machine Learning Engineer

Seattle, WA

About the Role

We are looking for a highly motivated Machine Learning Engineer to join the Uber Eats Search and Discovery Team. You will play a critical role in enhancing the search experience for millions of Uber Eats users worldwide. You will leverage your expertise in data analysis, machine learning, and Engineering to drive insights and optimize search algorithms, ultimately improving user satisfaction and operational efficiency.

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

  • Design, develop, and productionize machine learning (ML) solutions in the field of Search and Discovery , GenAI, QU/Ranking , MOO optimizations.
  • Productionize and deploy these models for real-world applications.
  • 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 Product and cross-functional teams to brainstorm new solutions and iterate on the product.
  • Mentor junior engineers.

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---- Basic Qualifications ----

  • Bachelor's or Master's in Computer Science, Statistics, or a related field or Equivalent Experience
  • Minimum 4 years of experience in industry with a strong focus on machine learning and optimization.
  • Experience with ML packages such as Tensorflow, PyTorch, 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.

---- Preferred Qualifications ----

  • Experience in the Search and Recommendations Field.
  • Experience in Query Understanding / Ranking or solving customer problems with NLP.

For San Francisco, CA-based roles: The base salary range for this role is USD$185,000 per year - USD$205,500 per year.

For Seattle, WA-based roles: The base salary range for this role is USD$185,000 per year - USD$205,500 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.

Uber is proud to be an Equal Opportunity/Affirmative Action 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): Seattle, WA, USA; San Francisco, CA, USA
Job ID: Uber-134927
Employment Type: Full Time

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