Uber
Consumer · Rideshare
Consumer · Rideshare
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 |
|---|---|---|
| Machine Learning Engineer II– Ranking & Recommendations Machine Learning Engineer II focused on building and deploying ML models for ranking and recommendation systems within Uber's shopping domain. The role involves developing ML models, productionizing them for real-world applications, and collaborating with product teams. Requires experience in ML model development, deployment, and big-data architecture. | Ship | 8 |
| Senior Machine Learning Engineer Senior ML Engineer at Uber's Applied AI team, focused on delivering end-to-end AI solutions for core business problems, including Generative AI, Computer Vision, and Personalization. The role involves building production-ready ML systems and infrastructure, from experimentation to deployment and monitoring, to power user and business-facing products. | Ship |
| 8 |
| Sr Applied Scientist Senior Applied Scientist at Uber to build and deploy ML/AI solutions in production, taking ideas from concept to real-world systems. The role involves end-to-end work from problem definition to production integration, focusing on classification, prediction, anomaly detection, and risk scoring. It also includes improving the reliability and robustness of AI systems, including LLM-based applications, and applying model adaptation techniques like fine-tuning. | ShipServe | 7 |
| Machine Learning Engineer II Machine Learning Engineer II at UberEats Feed, focusing on innovating and productionizing state-of-the-art recommendation models and building end-to-end large-scale ML systems for the HomeFeed Recommendation. The role involves improving ML quality, model serving, and data foundations. | Ship | 7 |
| Senior Machine Learning Engineer – Ranking & Recommendations (Generative AI) Senior Machine Learning Engineer role focused on building and productionizing Generative AI-powered ranking and recommendation systems for Uber's shopping platform. Requires strong ML experience, productionization skills, and expertise in big-data architecture and ML technologies. | ShipServe | 7 |
| Senior Machine Learning Engineer - Ads Uber's Ads ML team is seeking a Senior Machine Learning Engineer to optimize ad recommendations and auction mechanisms within their ecosystem. The role involves designing and implementing ML models, developing scalable ML pipelines, applying advanced ML techniques for targeting and delivery, and collaborating with cross-functional teams. The goal is to enhance user engagement and merchant benefits through data-driven insights and robust ML solutions, directly impacting Uber's growing Ads business strategy. | Ship | 7 |
| Staff Scientist Staff Applied Scientist on the Earner team at Uber, focusing on building the best platform for drivers and couriers. The role involves setting science strategy for personalization, marketplace efficiency, reliability, and experimentation guardrails. Responsibilities include designing and analyzing large-scale experiments, building statistical, optimization, and machine learning models, defining metrics and observability, leading multi-team initiatives, advancing causal inference and optimization frameworks, mentoring scientists, and communicating with leadership. Requires an M.S. or Ph.D. in a quantitative field with 8+ years of industry experience, deep expertise in statistical inference, experimental design, causal inference, machine learning, optimization, and proficiency in Python and SQL with production-minded code quality. | Ship | 7 |
| Manager II, Science - Delivery Manager II, Science for Uber Ads & Offers team, focusing on Ads Delivery & Optimization. This role involves leading a team of scientists to design and implement algorithms for Ads relevance, ranking, bidding, and pacing, driving strategic vision and execution for the Ads delivery product. Requires experience in Ad tech or marketplace industries and building Ads systems. | Ship | 7 |