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Uber

Connects people with rides, meals and groceries

Staff Machine Learning Engineer

Applied Machine LearningConfirmed live in the last 24 hours
Full-timeIn-person

About the Job

Requirements

  • A bachelor's degree or equivalent work experience in Computer Science, Machine Learning, Engineering, Mathematics, or a related discipline.
  • At least 5 years of professional experience designing, building, and operating production machine learning systems, including strong backend engineering across the full path from data to serving.
  • A track record of driving business impact beyond shipping features, including owning a product or product line and helping move metrics such as revenue, adoption, or customer value.
  • Fluency in Python for machine learning and a production systems language such as Go, Java, or C++, with the ability to build reliable services and run them in production.
  • Ability to find high-value problems, make decisions, and drive work independently in ambiguous, fast-moving environments.
  • Ability to align customers, product, and engineering around business growth.

Responsibilities

  • Build machine learning and backend systems that turn a vision into a product customers pay for and rely on.
  • Own a vertical end to end by finding opportunities, setting direction, and driving business metrics such as revenue, adoption, and customer value.
  • Prioritize in ambiguous situations, make decisions, and turn ideas into shipped, revenue-generating products with a product manager and a small senior team.
  • Serve as a trusted technical partner in customer relationships where relevant, and use customer insights to grow the account.
  • Raise execution and quality standards to enable the business to scale.

Desired Qualifications

  • Experience growing a product or business line in a startup or startup-like environment, owning outcomes end to end and treating revenue and customer growth as core responsibilities.
  • Experience applying machine learning to real-world data or evaluation domains, such as physical-world data collection, reinforcement learning environments and agentic evaluation, multilingual or audio data, or data quality and verification, with success measured by business impact rather than model metrics alone.
  • Direct experience with generative AI and large language model systems in production, including evaluation harnesses, model tuning, forced alignment or automatic speech recognition, or pipelines that keep a model in the loop.
  • Depth in one or more UAIS domains: real-world and physical-world data such as points of interest and embodied capture, agentic reinforcement learning environments, multilingual and multimodal machine learning, video and LiDAR annotation, or physical AI and robotics data.
  • A master's or PhD in Computer Science, Machine Learning, Engineering, Mathematics, or a related discipline.

About the Company

Uber

Connects people with rides, meals and groceries

Uber runs digital marketplaces that connect people seeking rides, meals and groceries with drivers, couriers and local merchants. Its Uber app includes private and shared rides, while Uber Eats lets customers order from restaurants and stores for delivery or pickup. The apps match requests with nearby service providers, handle payment and show trip or order progress, with revenue coming from service fees charged on transactions. Uber Freight connects businesses shipping goods with trucking companies and sells managed transportation services, extending the group's software beyond consumer trips. Founded in 2009, Uber is headquartered in San Francisco, California.

Company size
10,001+
Company stage
IPO
Headquarters
San Francisco, CA
Founded
2009

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