Uber
Consumer · Rideshare
Consumer · Rideshare
Currently tracking 25 active AI roles, down 34% versus the prior 4 weeks. Primary focus: Agent · Engineering. Salary range $142k–$336k (avg $220k).
Uber is actively hiring for 130 AI-related roles, with a significant focus on agents, which accounts for 40% of their open positions. Application roles also represent a substantial portion of their AI hiring at 29%. The majority of these roles are within Engineering, with the United States being the primary hiring country. Frequent technology tags include model serving, recommender systems, and agent orchestration, suggesting a direction towards deploying and managing AI systems.
Uber currently has 36 active AI-related roles in our index. The most common open titles are: Engineering Manager II, AV Labs, Engineering Manager II, Evaluation & Simulation - AV Labs, Engineering Manager II, Ranking and Recommendations, Grocery and Retail, Enterprise Applications Developer, Group Product Manager, AV Labs. Most positions are in Engineering and Product.
Uber's active AI hiring is concentrated in: agents (50%), data (19%), evaluation (11%). These categories follow a seven-stage AI lifecycle: data, pre-training, post-training, serving infrastructure, agents, evaluation, and application.
Uber is hiring AI talent in: United States (33 roles), Netherlands (2 roles), India (1 role).
Job postings at Uber most frequently mention: Machine Learning, Autonomous Driving, Computer Vision, Robotics, LLM Evaluation & Grading.
In the past 30 days, Uber has posted 10 new AI-related roles. That is a -69% change versus the prior 30 days (32 → 10).
| Title | Stage | AI score |
|---|---|---|
| Staff Data Scientist (Fraud, Risk) Uber is seeking a Staff Data Scientist for their Global Safety & Risk Team in Sao Paulo, Brazil. The role focuses on applying data analysis, machine learning, and statistical modeling to identify and prevent safety incidents. Key responsibilities include analyzing imbalanced datasets, designing and implementing binary classification models, generating insights from risk data, conducting complex experiments (Diff-in-Diff, Synthetic Controls), and defining success metrics. The role requires experience in building and deploying binary classification systems for high-stakes applications, experimental design beyond A/B testing, handling extreme class imbalance, and proficiency in Python and SQL. Experience with geospatial data analysis and real-time inference systems is preferred. | Ship | 7 |
| Senior Data Scientist - Applied AI Senior Data Scientist role focused on applied AI and ML for Uber's Discovery Science team. The role involves designing and implementing ML models for recommender systems, unifying business interests, and applying advanced techniques like Deep Learning and Reinforcement Learning to solve complex problems. It requires end-to-end ownership of models, from hypothesis to production debugging in low-latency environments. |
| Ship |
| 7 |
| Machine Learning Engineer II Machine Learning Engineer II at Uber on the Rider ML team, focused on developing and deploying ML infrastructure and ranking solutions for personalized rider experiences, optimizing homepage and product selection ranking with real-time, low-latency deep learning models. | Ship | 7 |
| Sr. Machine Learning Engineer Uber is seeking a Sr. Machine Learning Engineer to enhance rider experience through personalized recommendations and tailored services at scale. The role involves developing and deploying deep learning models for real-time, ultra-low latency applications, focusing on ranking solutions and ML infrastructure for rider engagement across various touchpoints. The position requires strong software engineering skills, expertise in ML methodologies, and experience with ML frameworks and data pipelines. | ShipServe | 7 |