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Private Full Time

Sr Machine Learning Engineer

Uber San Francisco, CA, United States
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Experience
Not specified
Qualification
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Posted
09 Oct 2026
Closing date
Check source
Salary
Not disclosed

Job information

About this opportunity

Employer: Uber | Original listing

Quick summary

Uber San Francisco, CA, United States Machine Learning Engineer Not specified

About the Role and Team

Engineering at Uber means building for real-world impact under real-world constraints. As a L5 MLE on the Pricing & Incentives team team, you will build innovative products and scalable systems that power our global marketplace. Our systems produce real-time decision signals and sophisticated algorithms that other critical systems depend on every second. The problems here are complex, the systems are massive, and the stakes are immediate.

What you'll do

  1. Requires advanced ML expertise to design machine learning models to jointly optimize demand levers (TDF, TSF, HVAs, EUP). This role is necessary to improve marketplace efficiency by modeling the coordination across pricing and incentive levers.
  2. Own the software lifecycle end-to-end: from design docs through production rollout, debugging live issues, and managing incidents.
  3. Collaborate across disciplines — Product, Applied Science, and Ops — to translate ambiguous marketplace problems into robust system designs.

Basic Qualifications

  1. 5+ years of professional software engineering experience in ML, statistics, or optimization techniques, distributed systems, or large-scale data processing.
  2. Proficiency in one or more programming languages (e.g., Go, Java, Python).
  3. Experience designing and operating high-throughput, low-latency services, and translating customer or business problems into system design.
  4. Bachelor's Degree (or equivalent experience) in Computer Science, Engineering, or a related technical field.

Preferred Qualifications

  1. Experience with marketplace, pricing, dispatch, forecasting, or other real-time decision systems.
  2. Familiarity with real-time data streaming (e.g., Kafka, Flink) or time-series forecasting pipelines.
  3. Demonstrated ability to exercise sound judgment on engineering trade-offs where algorithm behavior has direct business impact.

Listing details

Employer
Uber
Location
San Francisco, CA, United States
Structured address
San Francisco, CA, US
Category
Machine Learning Engineer
Base salary
Not disclosed
Valid through
Check official source
Reference
302444
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