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.
Currently tracking 95 active AI roles, down 34% versus the prior 4 weeks. Primary focus: Agent · Engineering. Salary range $142k–$336k (avg $224k).
Uber currently has 86 active AI-related roles in our index. The most common open titles are: Senior Software Engineer (3), 2026 PhD Applied Research Project (3 months), Aarhus, 2026 PhD Research Intern, India, 2026 PhD Software Engineering Internship, Security, Amsterdam, Agentic GTM Lead. Most positions are in Engineering and Product.
Uber's active AI hiring is concentrated in: agents (50%), application (19%), data (15%). 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 (67 roles), India (12 roles), Netherlands (7 roles), Denmark (1 role).
Job postings at Uber most frequently mention: Machine Learning, Production ML Systems, Autonomous Driving, Robotics, Generative AI.
In the past 30 days, Uber has posted 5 new AI-related roles. That is a -84% change versus the prior 30 days (32 → 5).
| 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 |
| 2026 PhD Research Intern, India Research Intern role focused on LLM post-training, data efficiency, and evaluation benchmarks, with a goal of publishable research and real-world impact at Uber AI Solutions. | Post-trainEval Gate | 9 |
| Senior Research Scientist, Generative AI This role focuses on foundational and applied research in Generative AI, specifically optimizing AI Solutions gig marketplace through intelligent matching, accelerating human-in-the-loop data annotation, and developing automated evaluation systems. The candidate will drive research in LLM post-training, data efficiency, and benchmark design, with a strong emphasis on publication in top-tier AI/ML conferences. | Post-train | 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 |
| 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 |
| 2026 PhD Applied Research Project (3 months), Aarhus PhD intern role focused on applied research in reliability and efficiency for Uber's core infrastructure. Projects involve optimizing systems, building risk scoring models, classifying incident data, advancing workflow versioning, and applying Generative AI or analysis techniques to prevent regressions. The role bridges novel research with production impact, requiring ownership from ideation to implementation. | AgentEval Gate | 7 |