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 |
|---|---|---|
| Senior Machine Learning Engineer - AV Foundation, AV Labs This role is for a Senior Machine Learning Engineer in Uber's AV Labs, focusing on frontier research for autonomous vehicles. The engineer will design and develop novel techniques, lead the model lifecycle, and publish original research. The role involves working with real-world driving data at scale and aims to advance autonomous vehicle technology through advanced ML and computer vision. | PretrainPost-train | 10 |
| Machine Learning Engineer II - AV Foundation, AV Labs This role is for a Machine Learning Engineer II in Uber's AV Labs, focusing on frontier research for autonomous vehicles. The candidate will design and develop cutting-edge techniques, collaborate with engineering and product teams, and publish original research. The role requires a PhD or MS with equivalent experience in a related field, proficiency in Python and deep learning frameworks, and a strong publication record in top-tier CV and ML conferences. Experience with autonomous vehicle research, training multimodal LLMs, and specific areas like 3D perception, diffusion models, and world models are preferred. |
| Pretrain |
| 9 |
| Sr. Scientist, UberEats Applied AI (Machine Learning) Scientist role focused on applying ML research, including Deep Learning, Reinforcement Learning, and GenAI, to build and optimize recommender systems for UberEats. The role involves designing algorithms, leading ML initiatives, conducting experiments, and owning the ML workflow from hypothesis to production, with a focus on real-time, low-latency systems. | ShipAgent | 8 |
| Sr Scientist, Tech This role focuses on designing, executing, and analyzing large-scale experiments for Uber Eats and Uber Rides, performing analytical deep dives into user behavior, conversion funnels, personalization, and retention. The scientist will design frameworks for optimizing business objectives, collaborate with cross-functional teams, and present findings to leadership. Requires experience in experimental design, causal inference, SQL, Python/R, funnel optimization, ML model development, and data processing workflows. | Ship | 7 |
| Staff Scientist, Rider Personalization The role focuses on rider personalization and ranking systems, implying the development and deployment of AI/ML models to improve user experience and engagement within Uber's consumer platform. | Ship | 7 |
| Scientist II, Tech Scientist II role focused on developing and analyzing ML models and optimization algorithms for Uber's mobility matching system, involving experimental design, causal inference, and large-scale data analysis to improve trip fulfillment and ETAs. | Agent | 7 |