Uber

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

This role focuses on building and scaling end-to-end localization workflows that integrate ML/LLM systems into Uber's global platform. It involves evaluating and operationalizing MT and LLM solutions, partnering with Engineering and MLOps to translate experimental AI into production-grade systems, and driving continuous improvement through quality frameworks.

This role focuses on building and evaluating models to predict and mitigate road safety risks using telematics and other data. It involves designing and executing experiments to test the effectiveness of these models and evaluations, working cross-functionally with product and operations teams.

Develop and improve GenAI-powered AI agents for customer personas, applying ML, causal inference, and experimentation to drive business impact. Collaborate with engineering and stakeholders, ensuring data quality and communicating insights.

Software Engineer I role at Uber focused on building a GenAI Bot for customer support, involving design, development, and testing of software applications, with a focus on integrating AI components into the existing system.

Senior ML Engineer role focused on building and productionizing ML models for Uber's Offers team, enhancing personalization and promotions. The role involves owning the end-to-end ML lifecycle, from data pipelines to low-latency serving, and collaborating cross-functionally to drive business impact.

This role focuses on building AI-driven software factories to automate engineering work by orchestrating agents and workflows using LLMs and CLIs. It also involves designing prompting and validation loops for AI-generated output within the Uber Direct Logistics team.

Senior Software Engineer to build and scale an AI-powered customer engagement platform using LLM prompting and backend services to deliver conversational assistants for millions of users.

Staff Software Engineer role focused on developing and operating security services and frameworks using ML/GenAI for Uber's products and platforms. Responsibilities include building ML-powered security systems for detection, classification, and risk scoring, developing backend infrastructure and ETL pipelines for security analytics, and productionizing ML models for security use cases. Requires experience with distributed systems, machine learning, and Golang/SQL/Python.

Senior Machine Learning Engineer for Uber's Customer Obsession team, focusing on enhancing customer support experience and driving cost savings through ML solutions. The role involves designing, developing, and productionizing generative AI, agentic AI, and NLP models, with a strong emphasis on experimental design and collaboration.

This role focuses on building ML models and AI agents for Uber's fares platform, which processes over $190B in gross bookings annually. The scientist will leverage experiment design, causal inference, and optimization techniques to solve problems in pricing, policy design, and defect reduction, influencing product strategy and automating data science workflows.

Machine Learning Engineer II at UberEats Feed, focusing on building and productionizing state-of-the-art recommendation models and large-scale ML systems. The role involves improving model quality, serving foundations, and data foundations for the UberEats Feed, which is the front door for users and merchants. Requires expertise in deep learning, recommendation systems, or optimization algorithms, and experience with ML frameworks and productionizing ML systems.

Software Engineer II ML on the Merchant Intelligence team at Uber Eats, focusing on building and productionizing ML models and scalable ML pipelines for merchant data processing, entity resolution, and feature engineering. The role involves improving data quality and serving critical use cases like sales outreach, onboarding, ads, and feed optimization.

This role focuses on developing and productionizing AI/ML models for Uber's core security engineering, specifically in access management, identity, and authorization. The engineer will translate security needs into AI-first solutions, integrate ML systems, and mentor junior engineers. Requires strong experience in ML model development, productionization, and familiarity with security contexts.

Senior Staff Engineer, Tech Lead for Uber's Matching & Segmentation organization, focusing on ML-powered systems for real-time rider-driver matching and marketplace segmentation. The role involves architecting, developing, and deploying ML and optimization systems at scale, leading cross-org initiatives, and mentoring engineers. Experience with backend development, distributed systems, ML systems, and optimization algorithms is required.

Develops and analyzes ML models and optimization algorithms for Uber's mobility matching system, focusing on improving trip fulfillment efficiency and reliability. Requires strong quantitative skills, experimental design, and causal inference.

Senior ML Engineer on the Content Platform team at Uber, focusing on building core ML capabilities for a customer support chatbot (Nova). The role involves improving response quality through observability, retrieval, ranking algorithms, and content strategies. Key responsibilities include defining observability and evaluation frameworks, developing retrieval and ranking algorithms (semantic search, RAG), building feedback loops, and collaborating with stakeholders to deliver production systems.

Senior ML Engineer role focused on building AI-driven security systems for Uber's Zero Trust Architecture. The role involves translating security needs into ML problems, developing and productionizing ML models for real-time risk-adaptive decisions, and integrating these systems into critical access pathways. This is a greenfield opportunity at the intersection of ML, security, and infrastructure.

Senior Scientist role focused on developing and deploying machine learning models for Uber's Maps products, including location search, route optimization, and travel time predictions. The role involves data analysis, experimental design, and building data-driven product enhancements.

Senior Scientist role focused on optimizing merchant selection and pricing models for Uber's Delivery business. This involves leading data scientists, designing A/B experiments, collaborating with cross-functional teams, generating insights from large datasets, and productionizing models. Requires strong analytical skills, ML development experience, and leadership capabilities.

Senior ML Engineer at Uber's Places Data Team, focusing on building production ML systems for places matching, attribute inference, summarization, and friction detection using classical ML, deep learning, and generative AI. Responsibilities include end-to-end ML solution development, experimentation, and mentoring junior engineers.

Director of Engineering for Uber's Marketplace team, leading a team of 40 engineers and applied scientists. The role focuses on building and leading the tech and systems for driver pricing and matching, including ML modeling, optimization, and backend systems. Requires strong management experience and a background in software engineering with ML/optimization.

Develops and analyzes ML models and optimization algorithms for Uber's mobility matching system, focusing on improving trip fulfillment, reliability, and ETAs. Collaborates with cross-functional teams to drive system development from concept to production.

Senior Staff Engineer role focused on Competitive Intelligence at Uber, involving extracting insights from market data and building defenses against scraping and data abuse. This includes adversarial machine learning and bot detection. The role requires leading technical vision, system design, and mentoring engineers, with a focus on high-stakes ambiguity and technical complexity.