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 |
|---|---|---|
| Staff Machine Learning Engineer - AV Labs Staff ML Engineer at Uber's AV Labs focused on Physical AI, developing advanced autonomy algorithms and models to add semantics to driving data. The role involves leading the technical roadmap for ML systems, designing large-scale ML systems, mentoring engineers, and evolving ML infrastructure for autonomous driving. | Data | 9 |
| Director, Engineering - AV Labs Director of Engineering role focused on leading the development of AI models, algorithms, and semantic engines for Uber's autonomous vehicle data capabilities. The role involves building advanced AI foundation models and scalable algorithms that process multi-modal sensor data to enrich L4 data and evaluation engines for autonomous driving. | DataAgent |
| 9 |
| Sr Staff Agentic Systems Engineer Uber is seeking a Sr Staff Agentic Systems Engineer to build the infrastructure for Agentic Dev Environments (ADEs), where AI agents are first-class participants in the software development lifecycle. The role involves designing and shipping the skill pack framework, building the multi-agent runtime with persistent background agents and swarm orchestration, developing AI-powered code intelligence, and owning the MCP platform layer for unified context infrastructure. The engineer will set technical direction for agentic infrastructure, define architecture and trust models, and mentor engineers in agentic fluency, working at Uber's scale across multiple monorepos and microservices. | Agent | 9 |
| Senior Staff Machine Learning Engineer – Moonshot AI Senior Staff ML Engineer for Uber's Moonshot AI team, focusing on building an enterprise AI data platform. Responsibilities include marketplace optimization, custom model development for annotation workflows (audio, video, text), automated quality evaluation using GenAI/LLM-as-Judge, and ML research. The role involves end-to-end ownership from research to production, technical leadership, and mentoring. | AgentPost-train | 9 |
| Principal Machine Learning Engineer - AV Labs Principal ML Engineer for Uber's AV Labs, focusing on Physical AI. The role involves building advanced autonomy algorithms and models to add semantics to driving data, enabling better data mining, scene understanding, and causal modeling of vehicle behavior. The primary focus is on enriching L4 data for an evaluation engine, with a secondary focus on agentic systems. | DataAgent | 9 |
| 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 |
| Staff ML Engineer, Generative AI Staff ML Engineer to architect, productionize, and scale an autonomous support agent that resolves customer issues end-to-end, focusing on LLM orchestration, evaluation, safety guardrails, and cost efficiency. | Agent | 9 |
| Senior Manager, Technical Program Management, GenAI Senior Manager, Technical Program Management, GenAI role at Uber AI Solutions. This role involves managing and scaling a team of TPMs to deliver complex AI training and evaluation services for frontier AI labs and AI-native companies. Responsibilities include shaping solutions, defining delivery models, establishing governance, ensuring high-quality execution, and building AI service capability and delivery maturity. Requires strong technical judgment, people leadership, program delivery expertise, and fluency in AI model training and evaluation. | Post-trainAgent | 8 |
| Manager II, Technical Program Management, GenAI Manager II, Technical Program Management, GenAI role at Uber AI Solutions. This senior, customer-facing leadership position involves managing and scaling a team of TPMs responsible for delivering complex AI training and evaluation services. The role requires partnering with various internal and external stakeholders to shape solutions, define delivery models, and ensure high-quality execution, with a strong emphasis on technical judgment, people leadership, and program delivery expertise in the AI model training and evaluation ecosystem. | Eval GateData | 8 |
| Software Engineer II - AV Labs Software Engineer II for Uber's AV Labs, focusing on Physical AI to build autonomy algorithms for enriching autonomous driving data. Responsibilities include algorithm development for semantic meaning extraction, system design for onboard systems, and defining requirements for evaluation datasets. | DataAgent | 8 |
| Senior Engineering Manager, AV Labs Senior Engineering Manager for Uber's AV Labs, leading a team focused on AI models and behavioral causality for autonomous driving data. The role involves building and managing ML engineers and researchers to develop foundation models for complex urban edge cases, enriching L4 data lake with semantic meaning from multi-modal sensor data, and contributing to the L4 data and evaluation engine. | AgentEval Gate | 8 |
| Staff AI Security Engineer - (Agentic Systems) Uber is seeking a Staff Security Engineer to join the Cyber Defense team, focusing on developing next-generation security platforms that leverage AI/ML/GenAI. The role involves architecting and implementing an AI-orchestrated attack platform and autonomous security agents for threat hunting and incident response, as well as defining secure environments for AI model development. The position requires strong software engineering and distributed systems expertise, with a focus on building scalable, high-availability security solutions. | Agent | 8 |
| Lead, Applied AI Lead Applied AI role focused on architecting and scaling intelligent automation solutions for Uber Advertising's Measurement Science function. The role involves building production AI applications end-to-end, designing AI agents and RAG systems, establishing AI safety and reliability practices, and building evaluation infrastructure. Requires strong Python, SQL, and experience with AI orchestration frameworks and LLM integration. | AgentEval Gate | 8 |
| Graduate 2026 PhD Software Engineer II (AV Labs), United States This role focuses on developing algorithms and foundation models for Physical AI in autonomous vehicles. The primary goal is to extract high-fidelity semantic meaning from complex urban edge cases to enrich L4 data lakes, optimize dataset quality for ML acceleration through advanced sensor data processing and auto-labeling, and implement scalable ML systems. The role involves collaboration with platform, product, and security engineering teams. | DataPost-train | 8 |
| Senior Software Engineer - AV Labs Senior Software Engineer for Uber's AV Labs, focusing on Physical AI to build autonomy algorithms that extract semantic meaning from driving data for L4 data lake enrichment. Responsibilities include algorithm development, systems architecture, technical leadership, and cross-functional collaboration with ML and platform teams. | DataAgent | 8 |
| Sr Software Engineer Senior Software Engineer at Uber focused on designing, developing, and deploying Machine Learning models for ranking and recommendation systems. The role involves building real-time data pipelines, feature engineering, model optimization, and optimizing inference for large deep learning models in a large-scale, real-world application context. | AgentServe | 8 |
| Applied Scientist Applied Scientist at Uber focused on building and productionizing ML/AI solutions for identity fraud detection and prevention on the Uber platform. The role involves applying various ML algorithms, including LLMs and generative AI, NLP, and time-series forecasting, to protect the platform at scale. | Ship | 8 |
| Senior Machine Learning Engineer – AV Labs Senior ML Engineer at Uber's AV Labs focused on Physical AI, developing autonomy algorithms and models to add semantics to driving data, enrich L4 data lake, and optimize datasets for ML technologies in the autonomous driving domain. | DataAgent | 8 |
| Principal Engineer - Marketplace Principal Engineer role focused on leading ML innovation in Uber's Driver Pricing organization. The role involves architecting and building next-generation ML systems for real-time pricing optimization, supply-demand balancing, and driver behavior modeling at scale. Key responsibilities include technical leadership, driving research in causal ML, reinforcement learning, and algorithmic game theory, owning the end-to-end ML model lifecycle, and building scalable ML infrastructure. The role requires expertise in modern ML frameworks, distributed computing, and various ML areas, with a strong emphasis on production deployment and measurable business impact. | AgentPost-train | 8 |
| Staff Machine Learning Engineer Uber's Applied AI team is seeking a Staff ML Engineer to design, implement, and scale high-impact AI solutions, focusing on Generative AI, Computer Vision, and Personalization. The role involves leading technical projects, influencing ML system architecture, and collaborating cross-functionally to deliver AI-powered features from ideation to production. | Ship | 8 |
| Engineering Manager II, Computer Vision - Applied AI Engineering Manager II for Computer Vision within Applied AI at Uber, leading a team to develop state-of-the-art vision and multimodal systems for production applications like document intelligence and onboarding automation. Responsibilities include driving technical strategy, managing engineers, and ensuring delivery of scalable AI solutions. | ShipPost-train | 8 |
| Security Engineer (AI & Agentic Systems) Uber is seeking an AI Red Team Engineer to identify and mitigate security risks in AI systems, particularly agentic and autonomous AI. The role involves designing and executing adversarial red-teaming exercises, analyzing agent workflows, and collaborating with AI teams to implement defenses. This is an offensive security role focused on AI-native vulnerabilities. | Agent | 8 |
| 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 |
| Staff ML Engineer - GenAI Staff ML Engineer focused on designing, developing, and productionizing Conversational GenAI solutions for customer support at Uber Eats, aiming for significant cost savings and improved user experience. The role involves agentic AI design, NLP, distillation, experimentation, and technical leadership. | AgentPost-train | 8 |
| Software Engineer II - Machine Learning Uber is seeking a Senior ML Engineer to build and scale an autonomous support agent for customer service. The role involves LLM orchestration, evaluation, safety guardrails, and ensuring reliability and cost efficiency in production systems handling millions of conversations. The engineer will also advance retrieval and reasoning pipelines and establish evaluation frameworks. | AgentEval Gate | 8 |
| Senior Machine Learning Engineer - Applied AI Senior ML Engineer role focused on building and deploying production-ready ML systems, including generative AI, computer vision, and personalization, to power core Uber products. The role involves the full ML lifecycle from experimentation to monitoring and emphasizes delivering end-to-end AI solutions. | 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 |
| Engineering Manager II, Marketplace Pricing Engineering Manager role focused on leading a team to design, develop, and productionize advanced ML models and pricing algorithms for Uber's Marketplace. The role involves real-time multi-objective optimizations, deep learning, causal modeling, and reinforcement learning for large-scale distributed systems serving billions of trips, with a focus on providing earnings opportunities for drivers. | ShipAgent | 8 |
| Sr. Staff Engineer (Conversational/Voice AI) Senior Staff Engineer to architect, productionize, and scale an autonomous support agent for Uber's Customer Obsession team, focusing on mobile, web, and voice channels. The role involves end-to-end agent architecture, shipping production systems with high reliability, leading voice agent initiatives, advancing retrieval and reasoning pipelines, establishing evaluation frameworks, driving automation, and mentoring engineers. | AgentServe | 8 |
| Principal Engineer - AI Tools Principal Engineer to lead the strategy and architecture of AI-powered developer tools at Uber, impacting thousands of engineers across the entire software development lifecycle. The role involves designing and implementing novel systems using LLMs and ML to improve developer velocity, code quality, and enable new agentic AI features. | Agent | 8 |
| Sr Staff ML Engineer - Applied AI The Applied AI team at Uber is seeking a Sr Staff ML Engineer to define the multi-year technical vision and architecture for foundation models powering discovery experiences across Mobility and Delivery. This role will focus on building a common semantic backbone for understanding users, places, merchants, items, and behavioral patterns, which will power personalization, search, agents, automation, and decision systems. The engineer will set long-term technical direction, drive alignment on strategy, and deliver measurable impact at global scale. | Post-trainAgent | 8 |
| Staff Machine Learning Engineer - Applied AI Staff ML Engineer to define and lead the foundation model strategy for AI-native discovery experiences across Uber's Mobility and Delivery platforms, focusing on Search, Recommendations, and Conversational AI. The role involves end-to-end technical strategy, architecture decisions, leading cross-team initiatives, defining investment areas (build vs fine-tune vs partner), and mentoring senior engineers. | Agent | 8 |
| Head of EMEA Risk Operations Lead Uber's regional fraud strategy and operational execution in EMEA, focusing on deploying and operationalizing AI-enabled tools to detect, investigate, and prevent fraud. This role involves shaping product roadmaps, building systems for proactive risk posture, and navigating complex regulatory environments. | Agent | 7 |
| Machine Learning Engineer ML Engineer role focused on building and deploying ML models for dynamic, risk-adaptive security systems within Uber's Zero Trust Architecture. The role involves framing security problems as ML tasks, engineering features, deploying ML pipelines, and integrating ML into authentication and authorization systems, with a focus on securing humans and AI agents. | Agent | 7 |
| Senior Software Engineer – AV Labs Senior Software Engineer for Uber's AV Labs, focusing on Physical AI to build autonomy algorithms for data mining, scene understanding, and causal modeling of ego vehicle behavior using real-world driving data. Requires C++ and Linux proficiency, with preferred experience in Autonomous Driving, safety-critical systems, and Python. | Data | 7 |
| Sr Software Engineer - AI Platform (Michelangelo) Uber's ML Serving team is seeking a Senior Software Engineer to build and operate large-scale, low-latency systems for real-time ML and generative AI inference. The role involves leading the design and ownership of critical serving services and frameworks, partnering with ML engineers to productionize models, and improving system reliability and performance. | Serve | 7 |
| Senior Scientist, Rider Personalization This role focuses on enhancing the Rider app's personalization AIML experience by leveraging data science and analysis to measure and optimize recommendation systems. The candidate will define and build metrics, ensure explainability and observability, design and analyze experiments, and design and build agentic AI to automate data science workflows. The goal is to improve user satisfaction and drive business growth through impactful personalization. | Agent | 7 |
| Senior Machine Learning Engineer Uber is seeking a Senior Machine Learning Engineer for their Customer Obsession team to design, develop, and productionize ML solutions for customer support. The role involves generative AI, agentic AI, NLP, and distillation techniques to enhance customer experience and achieve cost savings. | AgentPost-train | 7 |
| Security Engineer II - Threat Modeling & AI Security Engineer focused on red teaming AI agents and developer tools, identifying vulnerabilities, and driving mitigation efforts. The role involves translating AI security standards into controls, scaling testing with automation, and communicating risk to stakeholders. | Agent | 7 |
| Privacy Technologist II - AI This role involves performing technical privacy reviews of engineering design documents, managing anonymization pipelines, and evaluating/improving AI-powered review tooling. The focus is on driving the privacy aspects of AI automation and ensuring safe handling of sensitive data within AI systems, particularly agentic AI and GenAI. | Agent | 7 |
| Lead, Data Governance & AI Readiness Lead for Data Governance and AI Readiness on the Customer Support Data team at Uber. This role focuses on ensuring customer support data is reliable, consistent, trusted, and fit for purpose for both human decision-making and AI-driven use cases like analytics, copilots, and agentic AI. Responsibilities include establishing and enforcing data quality, observability, lineage, metadata, and semantic clarity standards, with a specific emphasis on preparing data for AI consumption (retrieval, summarization, recommendation, automation, training, evaluation). The role also involves driving adoption of governance standards and embedding shift-left governance principles. | DataAgent | 7 |
| 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 |
| Staff Software Engineer Staff Software Engineer to lead the design and development of systems at the intersection of Security and AI, focusing on proactive detection, prevention, and response to security and privacy risks. The role involves owning critical architecture, driving complex initiatives, and setting engineering standards, with a focus on leveraging ML/AI techniques to improve security signal quality and scale detection capabilities. | Agent | 7 |
| Engineering Manager II - AI & Security Engineering Manager II to lead a team at the intersection of Security and AI. The team builds systems that proactively detect, prevent, and respond to security and privacy risks across Uber's platform. The role involves defining strategy, scaling systems, and leading a multidisciplinary team of engineers and applied scientists to secure modern application stacks, data systems, and emerging AI-powered products. Key responsibilities include leading and growing the team, defining the roadmap for security and AI-driven systems, building intelligent systems for risk automation, securing AI-powered applications against threats, partnering with other teams to embed security controls, and scaling systems to improve security posture. | Agent | 7 |
| Senior Scientist, Matching The role focuses on algorithmic decisions, experimentation, measurement, and data strategy for Uber's global airports, specifically within the Matching group. The primary responsibility is to build systems that determine the optimal way to fulfill trips by deciding which earners to send offers to and when. This involves developing data-driven insights, designing and analyzing experiments, and contributing to the development of optimization algorithms and ML models for mobility matching at Uber's scale. | Ship | 7 |
| Staff Software Engineer Staff Software Engineer with advanced ML expertise to join the Data Governance team within Engineering Security. Responsible for designing, developing, and managing distributed systems to protect large-scale data infrastructure, specifically focusing on detecting and addressing data security threats related to AI agents. This role involves building user-facing products, managing high-throughput systems, and developing intelligent fraud prevention strategies using AI and Data Security techniques, with a technical leadership component. | Agent | 7 |
| Scientist II - Reservations Scientist II role focused on improving the Reserve product by transitioning from heuristic-based decision making to building machine learning models for real-time decisions, enhancing driver and rider experience, and piloting new use cases. The role involves designing roadmaps, running large-scale experiments, and analyzing business/user behavior trends. | Ship | 7 |
| Software Engineer II - Michelangelo Software Engineer II on Uber's ML Training team, responsible for designing and building core components of large-scale distributed training systems for multi-GPU/TPU environments within the Michelangelo AI platform. Focuses on ML infrastructure and enabling efficient, reliable, and scalable model development. | Pretrain | 7 |
| Staff Scientist, Rider Booking Experience This role focuses on building and evaluating AI booking agents and related ML systems for Uber's core mobility business. It involves designing experiments, developing models, and analyzing user behavior to improve the rider experience and drive growth. The role also includes shaping strategic vision, establishing metrics, and leading cross-functional initiatives. | Agent | 7 |
| Staff Scientist - Reservations The Reservations data science team at Uber is seeking a Staff Scientist to own the experience and algorithms powering the Uber Reserve Product. This role involves optimizing user experience, matching, dispatch, and pricing algorithms by transitioning from heuristic-based decision making to building and deploying machine learning models. The focus is on driving efficiency, improving unit economics, and increasing adoption and growth through data science methodologies, causal inference, large-scale experiments, and presenting findings to executive audiences. The role requires strong programming skills, MLOps practices, and experience in experimental design and analysis. | Ship | 7 |