Uber

Senior Staff ML Engineer focused on Account Integrity and fraud prevention using ML models. The role involves shaping the technical roadmap, designing and implementing end-to-end ML pipelines, and productionizing solutions at scale. Familiarity with multi-task learning, LLMs, and anomaly detection is preferred.

Machine Learning Engineer II focused on Dynamic Supply Pricing (DSP) at Uber, developing models, algorithms, and large-scale distributed systems for real-time driver pricing. The role involves designing, developing, and productionizing end-to-end ML solutions, including deep learning, causal modeling, and reinforcement learning, for a high-volume marketplace serving millions of drivers.

Staff ML Engineer role focused on developing and productionizing advanced ML models and pricing algorithms for Uber's Marketplace Pricing, involving deep learning, causal modeling, and reinforcement learning in large-scale distributed systems serving billions of trips.

Staff Machine Learning Engineer focused on pricing and incentives, designing and implementing ML models for dynamic pricing and incentive allocation at Uber scale. Responsibilities include shaping the technical roadmap, end-to-end ML pipeline ownership, and productionizing solutions.

Uber's Surge team is hiring a Staff ML Engineer focused on causal inference to build large-scale pricing optimization systems. The role involves training ML models with sparse data, designing experiments, and developing causal models for real-time marketplace conditions. This is a backend role with significant impact on rider experience and driver earnings.

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.

Staff Scientist role focused on designing and building core algorithmic components for Uber's Advertising and Offers platform, involving statistical, optimization, and machine learning models for auction, bidding, pacing, and ranking. The role requires understanding system performance, leading algorithm design, and collaborating with cross-functional teams to productionize solutions.

Senior Engineering Manager for Uber Eats Shopping ML team, focusing on personalization and discovery experiences. The role involves defining strategy, collaborating with cross-functional teams, developing scalable ML systems, and staying updated on industry trends. Requires significant experience in managing ML teams and applying ML to real-world problems, particularly in consumer-facing products.

Lead Product Manager for Uber's Seller Tech team, focusing on the end-to-end commercial platform. This role involves owning product strategy, roadmap, and execution for a multi-product domain, managing a team of PMs, and leading the design and integration of AI and agentic capabilities into the product surface. The goal is to translate business goals into product strategy and requirements for platform investments, ensuring scalability and architectural soundness.

Chief of Staff role partnering with a Regional General Manager for Delivery in APAC, focusing on strategy, operations, and team effectiveness. The role involves thought partnership, driving focus, orchestrating leadership team operations, and ensuring priorities translate into action. A key aspect is accelerating AI impact within the organization.

Staff Software Engineer on the Places Data Team at Uber, focusing on building and maintaining large-scale data pipelines for geospatial data (POI, Addresses, Building Footprints). The role involves data conflation, inference, and applying ML for matching and summarization, with a strong emphasis on technical leadership and end-to-end ownership.

This role is for a Sr Strategy & Planning Associate for Uber Eats Restaurants in ANZ. The role involves shaping and executing strategy, identifying growth opportunities, improving marketplace and P&L performance, and leading strategic projects. It requires strong analytical, strategic thinking, and stakeholder management skills. While the role leverages AI/ML tools, it does not involve building or shipping AI models.

Software Engineer II on the Incentive Platform team at Uber, focusing on building and scaling a business-critical, ML-powered incentive ecosystem for drivers and couriers. The role involves architecting and developing high-throughput, real-time distributed systems and ML inference infrastructure to optimize incentive generation and delivery.

This role is for a Sr. Technical Program Manager within Uber's Engineering Security organization, focusing on AI governance and AI agent oversight. The TPM will drive cross-functional reviews of security standards, support AI agent inventory and governance, coordinate AI red teaming activities, and manage security and privacy review programs. The role involves using and improving internal AI tooling for tasks like triage, assignment, and reporting, and ensuring AI agents are accurate and calibrated. It also includes managing a security champions network and performing cross-program analysis to drive improvements. The TPM will partner with senior leaders to shape AI governance across the engineering organization.

The Localization Program Manager will manage end-to-end localization of Uber products and external clients assets across all supported languages, ensuring on-time and high linguistic quality. This role involves partnering with various cross-functional teams, influencing product requirements, managing localization of different content types, identifying tool and process gaps, and working with vendors. Familiarity with technologies like MT, LLM, and GenAI is required.

This role focuses on improving operational efficiency and delivery quality for Uber Direct, a merchant-focused delivery service. It involves strategic planning, data analysis, cross-functional collaboration, and project management to optimize key business metrics. While the role uses AI tooling and works with data, it does not involve building or shipping AI models.

This role focuses on analyzing data, designing experiments, and building models to optimize Uber's rider pricing and incentives algorithms and platform. It involves understanding product performance, developing new metrics, and informing strategies for marketplace efficiency and reliability.

This role focuses on building predictive models and data infrastructure for sales operations, leveraging AI tools to enhance efficiency and deliver insights. It involves data engineering, analytical modeling, and creating automated pipelines to support global sales strategies.

This role leads operations for a proprietary supply channel within Uber AI Solutions, focusing on scaling programs for internal solutions and external enterprises. The goal is to establish leadership in the AI training space by managing operations, defining go-to-market plans, advising product teams, and ensuring cross-functional alignment for safety and reliability. The role involves tracking metrics and scaling the channel internationally.

This role focuses on optimizing the rider experience and driving growth in Uber's mobility business through data analysis, experimentation, and ML modeling. The scientist will develop AI systems to understand metric trends, optimize conversion funnels, and create personalized features and pricing models for riders.

This role focuses on optimizing Uber's marketplace at airports globally, using data to diagnose issues, evaluate changes, and improve reliability, conversion, and driver earnings. It involves cross-functional collaboration with operations, product, and engineering teams, and strengthening data foundations for airport performance reporting.

Staff Scientist role focused on identifying and solving complex business problems within the Airports and Travel segment at Uber. The role involves strategic problem finding, leading end-to-end data-driven solutions, advanced experimentation, defining business metrics, and influencing senior leadership. While the role mentions using AI/Agentic tools as a preferred qualification, its core function is not AI/ML development but rather applying data science and experimentation to business challenges.

This role focuses on optimizing employee experience with HR services through ServiceNow and AI-enabled self-service. The candidate will define strategy for leveraging ServiceNow, establish global knowledge standards for AI readiness, and drive AI-enabled initiatives like virtual agents and automated triage to enhance digital employee experience. The role also involves platform governance and ensuring compliance.

This role focuses on building and operating the infrastructure for Uber's Digital Sales Center (DSC), standardizing global operations, performance measurement, pipeline design, tooling, and automation. It involves partnering with Product and Engineering to scale AI-driven solutions within CRM workflows to improve seller productivity and reduce cost per acquisition.

This role is for a Regional Operations Manager at Uber, focusing on the Matching and Trip Radar systems in Latin America. The manager will analyze marketplace failures, review and recommend experiments for matching algorithms, lead local launches, build automation frameworks, and collaborate closely with Product and Engineering teams. The role requires strong analytical, technical fluency, and stakeholder management skills, with 5-7 years of experience.

Product Manager for Uber's AI-powered conversational support surfaces, focusing on the developer and user experience of the foundational platform and UX component library for AI assistants. The role involves building infrastructure for cross-functional teams to contribute to a shared UX library, ensuring cohesive and adaptable AI assistants. Responsibilities include roadmap contribution, customer experience advocacy, building platform foundations, driving developer adoption of agentic UX libraries, data-driven impact analysis, and executive communication.

This role is for a Senior Growth Strategy Manager at Uber Direct, focusing on driving long-term commercial relationships with restaurants in the UK. The responsibilities include developing growth plans, managing P&L, optimizing operations and commercials, performing data analysis, and piloting new strategic initiatives. The role requires strong analytical skills, commercial acumen, communication, project management, and stakeholder management abilities. While the role mentions comfort with AI tools, its core function is business growth and strategy, not AI/ML development.

This role leads real-time Autonomous Vehicle (AV) support operations, managing a large team and focusing on scaling operations through tooling, technology, and automation. It involves partnering with tech teams to improve workflows, systems, and decision-making, with a focus on future AI adoption and translating frontline signals into product and operational improvements.

This role focuses on account integrity within Uber's Safety & Identity Operations, involving identity verification, fraud detection, and risk mitigation. The manager will own problem discovery, root cause analysis, and develop solutions to strengthen platform integrity. Key responsibilities include analyzing data, improving policies/processes, partnering cross-functionally, designing detection signals, leveraging AI tools for efficiency, and building reporting. The role requires strong analytical and problem-solving skills, with experience in fraud/risk/identity problems and leveraging AI tools being preferred.

Lead Product Manager for Uber's AV Labs, focusing on building platforms to unlock real-world, long-tail driving data for autonomous vehicles. The role involves owning product strategy, roadmap, and execution for core AV Labs domains including machine learning and data platforms, translating technical goals into product requirements, and partnering closely with engineering and science teams.

This role is for an Applications Developer Engineer focused on the operational health, configuration, and lifecycle of Uber's core enterprise SaaS applications. The role involves managing application configurations, access, integrations, and automation, acting as a Super Admin, and resolving complex escalated issues. A key responsibility is designing and implementing automation and integration workflows using JavaScript, Python, APIs, and Enterprise AI applications like Gemini, ChatGPT, and Claude to reduce manual effort and improve reliability. The role requires strong programming skills in Python, JavaScript, Java, and SQL, and knowledge of databases like BigQuery and Apache Hive.

This role is for an Enterprise Applications Developer Engineer responsible for the operational health, configuration, and lifecycle of core enterprise SaaS applications at Uber. The role involves managing applications, resolving complex issues, leading incident response, and designing/implementing automation and integrations using various programming languages and Enterprise AI applications. The candidate will act as a primary technical owner and Super Admin for applications like Google Workspace, Zoom, Slack, and others, bridging IT Engineering, Service Desk, Security, and Business stakeholders.

This role focuses on developing and owning enterprise SaaS applications, including managing configurations, access, integrations, and lifecycle. A key responsibility is designing and implementing automation and integration workflows using JavaScript, Python, APIs, and Enterprise AI applications (Gemini, ChatGPT, Claude, Claude Code, MCP) to improve reliability and reduce manual effort. The role also involves acting as a Super Admin, leading incident response, and resolving complex escalated application issues.

Manager for Uber's Financial Operations Analytics team, focusing on leveraging AI and data analysis to drive strategic decisions. The role involves managing a team of analysts, owning the analytics lifecycle, utilizing predictive modeling, and driving automation through AI. Key responsibilities include stakeholder management, project oversight, team leadership, and championing the transition to AI Assistants for financial insights.

This role focuses on building prototype software solutions to automate business processes and drive operational efficiency using data and AI technologies. The candidate will leverage data to understand business problems, identify automation opportunities, conduct architecture and code reviews, and manage teams. The role involves developing end-to-end solutions for funnel optimization, user engagement, and user experience, and identifying use cases for machine learning and AI capabilities.

Software Engineer II role focused on building ML-driven solutions for the Earner lifecycle, including personalized experiences, acquisition, and retention. The role involves working with GenAI/LLMs, Deep Learning embeddings, Causal ML, and Multi-armed Bandits to drive business growth and optimize user touchpoints. The position requires designing and scaling backend services, collaborating with Data Science and Product teams, and ensuring system integrity.

This role focuses on people analytics, using data to answer business questions and influence decisions related to engagement, retention, performance, and organizational health. It involves analyzing employee survey data, building dashboards, and communicating insights. While the role mentions leveraging Generative AI tools, its core function is data analysis and consulting within the HR domain, not building or shipping AI models.

Staff Security Engineer to drive the development of next-generation security platforms, architecting and implementing industry-leading security solutions. The role involves leveraging automation and AI/ML to transform enterprise defense.

Staff Engineer on the Core Infrastructure Platform team at Uber, focusing on the architecture and evolution of systems powering Uber's global business. The role involves leading the development of backend solutions for cloud-native, secure, reliable, and hyperscale-efficient ecosystems, supporting massive compute demands for Generative AI and Autonomous Vehicle data. Responsibilities include architectural evolution, driving efficiency, modernizing for multi-cloud, integrating AIOps & Automation, championing security, and influencing cross-functional teams to support large-scale AI/ML workloads.

Senior Staff Software Engineer role focused on architecting and building Uber's Next-Generation Data Intelligence Platform, which includes unifying batch, streaming, and AI compute, revolutionizing storage and catalog management, and operationalizing agentic data intelligence. The role involves evolving large-scale persistence layers and integrating compute fabrics with vector databases and model-serving platforms.

Senior Staff Engineer to lead the technical strategy and evolution of Uber’s Core Infrastructure Platform, focusing on compute, foundations, and software networking. The role involves architecting for extreme scale, optimizing fleet utilization, scaling GPU pools for Generative AI, modernizing the data plane, and integrating AI-driven automation (AIOps) into the infrastructure.

Data Scientist role focused on people analytics, using quantitative methods including statistical modeling, causal inference, experimentation, and machine learning to understand employee behavior and inform strategic decisions. The role involves analyzing survey and behavioral data, improving measurement approaches, and communicating findings to stakeholders. Experience with GenAI tools for data analysis is a plus.

Director of Sales for Uber's Annual Plan, focusing on enterprise customers and driving revenue for Uber AI Solutions. This role requires understanding AI Solutions capabilities to demonstrate value, accelerate partnerships, and shape tech/ops direction. It involves building customer relationships, leading sales strategy, and managing a team of sales professionals.

Software Engineer at Uber responsible for designing and developing large-scale data systems, including databases, data warehouses, and big data platforms. The role involves building robust and scalable software solutions, designing and building scalable data pipelines for batch and real-time processing using tools like Apache Airflow, Spark, SQL, Kafka, and Flink. Key responsibilities include ensuring data quality, privacy, and compliance, championing data governance, driving automation, and collaborating with cross-functional teams. The role also requires staying updated on data engineering, Gen AI, and Cloud solutions to create innovative solutions and mentoring junior engineers.

Program Manager for Uber's Physical AI team, focusing on managing human-in-the-loop (HITL) operations for ML/AI projects, specifically 2D/3D LiDAR annotations, object detection, and semantic segmentation. Responsibilities include designing data pipelines, managing global vendor operations, developing SOPs, and analyzing program metrics to drive decisions and improve processes from pilot to full-scale deployment.

Staff Software Engineer role focused on architecting and scaling distributed backend systems for media ingestion, processing, intelligence, and delivery. The role involves improving performance, reliability, and cost efficiency of high-throughput media pipelines, and designing infrastructure for efficient integration and execution of ML inference workloads within these media systems. It also includes driving technical strategy and mentoring engineers.

Engineering Manager for Uber's Grocery & Retail Consumer Ranking Team, focusing on leading the evolution of the online ranking architecture and high-throughput serving stack. The role involves building the engine for seamless shopping experiences, optimizing for latency, cost, and availability, and partnering with Data Science and ML Engineering to integrate state-of-the-art models into a production environment at scale. Responsibilities include leading backend and ML engineers, owning the roadmap, driving reliability and performance, evolving data flow, setting technical vision for ranking infra, and scaling experimentation capabilities.