Uber machine learning engineer jobs
- Open jobs
- 101
- First seen in the last 30 days
- 101
- Median days open, by our records
- 11
- Reposted
- 16%
What these jobs say
- Where
- San Francisco, California 34, Sunnyvale, California 26, Seattle, Washington 21, New York 18, Chicago, Illinois 2
- Work setting
- Hybrid 87
- Level
- Mid-level 13, Senior 37, Staff 51
- Tools named most
- Python 71, Java 54, Spark 49, C++ 30, Scala 20, Hive 17, C 15, SQL 8
- Experience asked
- 6 years at least, at the median of 98 jobs that say
Teams hiring and what the work is
- Earner Intelligence team
Build conversational and ambient agents, plus statistical, optimization and ML models, that help drivers and couriers (earners) onboard, activate and stay active on Uber.
Sr Machine Learning Engineer - Mobility Simulation and Planning (MSP) Infra team
Build shared ML frameworks, distributed training and simulation execution, and tooling that move scientists' models from experiments to production for Uber's pricing and incentive planning.
Sr Software Engineer - ML Infrastructure - Uber Marketplace Rider Pricing team
Build and scale ML models and serving systems that set rider prices and target promotions for Uber riders.
Software Engineer II - Machine Learning - Rider Pricing team within Uber Marketplace
Build and scale ML models and optimization systems that set rider prices and target promotions and discounts for Uber's rides.
Software Engineer II - Machine Learning - Marketplace Matching team
Build and productionize real-time ML and optimization systems that decide how riders and drivers get matched across Uber's marketplace.
Staff ML Engineer (Optimization) - Consumer Incentives
Build and launch ML-powered and distributed systems that personalize consumer incentives across grocery and food, from scoping through post-launch maintenance.
Sr Machine Learning Engineer - Consumer Incentives
The newest 40 of 101 open jobs
Counts cover every open machine learning engineer job we read from Uber's own careers site, last checked Nov 14, 2026. The role is the one the work describes, whatever the title says. Ages use the day we first saw each job. We count a repost when the same title and location comes back as a new listing within 60 days of the last one coming down. Some hiring systems expire listings on a schedule, so repost rates vary by system. How we count Report an error