Senior Machine Learning Engineer - Rider Pricing & Incentives

Uber Uber · Consumer · San Francisco, CA +1 · Engineering

Senior Machine Learning Engineer at Uber focused on Rider Pricing & Incentives. The role involves developing and implementing advanced ML and optimization techniques to drive revenue and ridership growth. Key responsibilities include improving pricing and promotion algorithms, owning the end-to-end problem, and mentoring junior team members. Requires expertise in deep learning, generative AI, causal modeling, and reinforcement learning, applied to large-scale data systems.

What you'd actually do

  1. Take a lead on pricing ML and optimization problems, by developing and implementing new machine learning and optimization techniques powering billions of rides around the world, and helping riders achieve their mobility needs.
  2. Improve the performance of models and algorithms powering pricing algorithms and promotion targeting.
  3. Own the problem E2E, including working with cross-functional teams to define the product and/or technical roadmap.
  4. Mentor more junior team members by role modeling ML best practices.

Skills

Required

  • Masters degree in Computer Science, Engineering, Mathematics, or a related field, with 5+ years of full-time engineering experience.
  • Proficiency in one or more programming languages (e.g., C, C++, Java, Python, Go).
  • Experience with machine learning and optimization algorithms.

Nice to have

  • PhD in Computer Science, Engineering, Mathematics, or a related field, with 2+ years of full-time engineering experience.
  • Experience solving complex business problems by translating them into machine learning and optimization solutions.
  • Familiarity with large-scale data systems (e.g., Spark, Hive) and experience building production-ready algorithmic systems.
  • Strong background in deep learning, generative AI, causal modeling, and reinforcement learning.

What the JD emphasized

  • advanced machine learning
  • deep learning
  • generative AI
  • causal modeling
  • reinforcement learning
  • production-ready algorithmic systems

Other signals

  • optimize pricing strategies
  • promotional systems
  • deep learning
  • generative AI
  • causal modeling
  • reinforcement learning