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 |
|---|---|---|
| Senior Applied Scientist – AI Red Teaming & Model Risk This role focuses on AI Red Teaming and Model Risk for LLMs and agentic AI systems. The scientist will design and execute experiments to uncover unsafe or harmful behaviors, develop evaluation frameworks, and define risk metrics beyond standard accuracy. They will analyze agent workflows and collaborate with security and platform teams to implement guardrails and mitigations. The role requires experience with LLMs, adversarial evaluation, and analyzing complex model behavior. | Eval GateAgent | 9 |
| Senior Product Manager - AI Quality Product Manager role focused on defining the future of agentic Conversational AI at Uber, specifically on building, testing, and scaling intelligent agents. The role involves working across AI reasoning, evaluation infrastructure, and platform tools for AI assistants in customer support environments. Requires strong product management fundamentals and practical experience building AI/LLM products, with a focus on agents, platforms, model evaluation, or intelligent tools. |
| Eval GateAgent |
| 7 |
| Principal Engineer - Evaluation & Simulation This role focuses on building and scaling large-scale simulation platforms for autonomous vehicle (AV) testing and validation. It involves designing high-fidelity simulation frameworks, integrating sensor data and behavioral models, defining evaluation metrics, and generating edge-case scenarios. The goal is to accelerate AI research and ensure safety benchmarking for AVs. | Eval GateAgent | 7 |
| Engineering Manager II, Evaluation & Simulation - AV Labs Engineering Manager II for Uber's AV Labs, focusing on defining the roadmap, metrics, and technical architecture for autonomous vehicle evaluation and simulation. The role involves building platforms to leverage real-world driving data for AV development and managing a team to achieve high technical excellence in this domain. | Eval Gate | 7 |
| Staff Systems Engineer, AM&D Partner Integration This role is a Staff Systems Engineer focused on evaluating the safety and maturity of Autonomous Vehicle (AV) partners integrating with Uber's platform. The primary responsibility is conducting technical safety due diligence, defining assessment criteria, performing Safety Risk Assessments (SRAs), and ensuring partner systems align with Uber's safety standards. A key aspect involves applying AI/ML responsibly to enhance safety validation and risk identification, while also translating regulatory requirements into engineering solutions. The role requires deep systems engineering expertise, experience in AV safety-critical systems, and strong communication skills for external partner interactions. | Eval Gate | 5 |
| Applied Scientist, Economist - Marketplace Fairness Applied Scientist role focused on assessing bias in products, projects, and machine learning models within Uber's marketplace. The role involves deep investigations, fairness testing, and contributing to AI/ML governance, working closely with legal, policy, and product teams. | Eval Gate | 5 |