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Uber's ML and Science division aims to optimize its marketplace by building systems that predict future events and match supply with demand efficiently, ultimately improving the experience for all participants, including earners, riders, and eaters.

Requirements

• PhD or equivalent experience in Computer Science, Machine Learning, Operations Research, Statistics, or other related quantitative fields or related field
• 4 years minimum of industry experience as a Machine Learning Engineer/Research Scientist with a strong focus on deep learning and probabilistic modeling.
• Proficiency in multiple object-oriented programming languages (e.g. Python, Go, Java, C++).
• Experience with any of the following: Spark, Hive, Kafka, Cassandra.
• Experience building and productionizing innovative end-to-end Machine Learning systems.
• Experience in exploratory data analysis, statistical modeling, hypothesis testing, and experimental design.
• 5+ years of industry experience in machine learning, including building and deploying ML models.

Responsibilities

• Build statistical, optimization, and machine learning models
• Develop innovative new earner incentives that earners for choosing our network and optimizing Uber’s new earner incentives spend
• Optimize Uber’s background check spend and onboarding funnel
• Design recommendation engines to recommend the most relevant earning opportunities and early lifecycle content
• Develop matching algorithms for driver to driver mentorship program
• Model and predict earner behaviors to improve earner experience throughout the onboarding funnel
• Work closely with multi-functional leads to develop technical vision, new methodological approaches, and drive team direction.

Other

• 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.
• 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.