Machining Engineer jobs at Über - 69 jobs

About the Role Uber is looking for a Senior Staff Engineer to lead the technical vision and execution for our Competitive Intelligence domain. A mission-critical space at the intersection of core business strategy and market-level decision systems such as pricing, incentives, and marketplace configuration. This role spans both offensive and defensive workstreams, requiring a systems thinker who can operate across high-stakes ambiguity and deep technical complexity. On the offensive side, you'll help us derive meaningful, actionable insight from incomplete, noisy, and often unreliable data sources to better understand market dynamics, competitor behavior, and pricing strategy. The systems you build must extract signal from chaos, integrating low-trust external data into internal pricing and incentive systems, and shaping coherent narratives that guide Uber's most strategic decisions. On the defensive front, you'll oversee the architecture and technical leadership needed to prevent scraping and data abuse, protecting the integrity of our platform and preserving the value of Uber's proprietary data. This includes work in adversarial machine learning, bot detection, and the design of resilient, real-time defenses at scale. This role offers a rare opportunity to define the direction of critical, high-impact systems that shape Uber's competitive edge, while mentoring engineers and partnering closely with senior leadership across product, engineering, data science, and security. What You Will Do Lead the design and development of systems that extract strategic insights from unreliable and fragmented market data Architect and guide the implementation of real-time defenses against scraping and data abuse, working on adversarial machine learning and bot detection solutions to protect Uber's data and platform integrity at scale. Drive critical cross-functional initiatives by partnering with data science, security, product, and engineering teams to align technical solutions with business priorities and long-term strategy. Mentor senior engineers across multiple teams, providing technical direction, setting engineering standards, and fostering a culture of high-quality system design, experimentation, and resilience. Basic Qualifications Master\'s Degree or equivalent in Computer Science, Engineering, Mathematics or related field with 7+yrs of software development experience. Proficiency in one of the programming languages (e.g. C, C++, Java, Python, or Go) Experience driving large-scale system modernization, performance optimizations, and deployment safety improvements. Ability to lead large technical initiatives and drive cross-team collaboration across platform, security, and infrastructure teams. Preferred Qualifications Cybersecurity Knowledge: Understanding of web scraping techniques and countermeasures. Awareness of network security, HTTP protocols, and API security. Experience in modern machine learning algorithms (e.g., tree-based techniques, supervised, deep, or probabilistic learning) Proficiency in unsupervised learning techniques, such as clustering, anomaly detection, and neural networks. Familiarity with supervised learning, as it often complements unsupervised methods. Understanding of feature engineering and dimensionality reduction. Familiarity with machine Learning software such as Tensorflow/Pytorch, Caffe, Scikit-Learn, or Spark MLLib Causal ML and Reinforcement Learning Ethical Considerations and Compliance: awareness of ethical issues and regulatory compliance related to data privacy and machine learning. For San Francisco, CA-based roles: The base salary range for this role is USD$267,000 per year - USD$297,000 per year. For Seattle, WA-based roles: The base salary range for this role is USD$267,000 per year - USD$297,000 per year. For all US locations, you will be eligible to participate in Uber's bonus program, and may be offered an equity award & other types of comp. You will also be eligible for various benefits. More details can be found at the following link: ***************************** Uber's mission is to reimagine the way the world moves for the better. Here, bold ideas create real-world impact, challenges drive growth, and speed fuels progress. What moves us, moves the world - let's move it forward, together. Uber is proud to be an Equal Opportunity employer. All qualified applicants will receive consideration for employment without regard to sex, gender identity, sexual orientation, race, color, religion, national origin, disability, protected Veteran status, age, or any other characteristic protected by law. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. If you have a disability or special need that requires accommodation, please let us know by completing this form. Offices continue to be central to collaboration and Uber's cultural identity. Unless formally approved to work fully remotely, Uber expects employees to spend at least half of their work time in their assigned office. For certain roles, such as those based at green-light hubs, employees are expected to be in-office for 100% of their time. Please speak with your recruiter to better understand in-office expectations for this role. #J-18808-Ljbffr

About the Role The mission of the Surge team is to maintain overall marketplace reliability by balancing supply/demand in real-time through dynamic pricing. We build scalable real-time systems to understand the state of the market, forecast future demand, make predictions using ML models, solve network optimization programs, and eventually make pricing decisions for each rider session. Surge plays a critical role in service of Uber's mission to make transport accessible. We generate billions of dollars in annual gross bookings for the company by optimizing network efficiency and make a significant contribution to driver earnings. In addition to pricing, the signals we generate are some of the most important features used in practically every optimization/ML system across Uber. Although we are a backend team, what we do has an outsized impact on our riders because prices and reliability are two of the most important elements of customer experience. What You'll Do You will work with a mixed team of Engineers, Operations Researchers, and Economists to build large-scale pricing optimization systems to set prices based on real-time marketplace conditions for Uber's rides products globally. Build and train machine learning models. Initiate new areas where machine learning models can make a large impact on the o Basic Qualifications PhD in relevant fields (CS, EE, Math, Stats, etc.) with a focus on Machine Learning. 4+ years of experience in an ML role with an emphasis on data and experiment driven model development. Expertise in deep learning and optimization algorithms. Experience with ML frameworks such as PyTorch and TensorFlow. Experience building and productionizing innovative end-to-end Machine Learning systems. Proficiency in one or more coding languages such as Python, Java, Go, or C++. Strong communication skills and can work effectively with cross-functional partners. Strong sense of ownership and tenacity toward hard machine-learning projects. Preferred Qualifications Experience in serving and monitoring online training systems such as real time recommendation systems. Experience designing and implementing novel metrics for performance evaluation. Experience handling time series data and time series forecasting (experience handling spatial temporal data is plus). Deep understanding of models such as VAE (Variational Auto Encoder), SSM (State space model), and Normalizing Flow. Experience in inference optimization and monitoring model performance efficiency and being able to identify bottlenecks. Proven track record in conducting experiments and tracking models in high-complexity environments. For San Francisco, CA-based roles: The base salary range for this role is USD$223,000 per year - USD$248,000 per year. For Sunnyvale, CA-based roles: The base salary range for this role is USD$223,000 per year - USD$248,000 per year. For all US locations, you will be eligible to participate in Uber's bonus program, and may be offered an equity award & other types of comp. You will also be eligible for various benefits. More details can be found at the following link ************************************** Uber's mission is to reimagine the way the world moves for the better. Here, bold ideas create real-world impact, challenges drive growth, and speed fuels progress. What moves us, moves the world - let's move it forward, together. Uber is proud to be an Equal Opportunity employer. All qualified applicants will receive consideration for employment without regard to sex, gender identity, sexual orientation, race, color, religion, national origin, disability, protected Veteran status, age, or any other characteristic protected by law. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. ". If you have a disability or special need that requires accommodation, please let us know by completing this form. Offices continue to be central to collaboration and Uber's cultural identity. Unless formally approved to work fully remotely, Uber expects employees to spend at least half of their work time in their assigned office. For certain roles, such as those based at green-light hubs, employees are expected to in-office for 100% of their time. Please speak with your recruiter to better understand in-office expectations for this role. #J-18808-Ljbffr

About the Role The Courier Pricing team sits within Uber's Delivery Marketplace org and plays a key role in shaping pricing across food, grocery, and other delivery verticals. We work closely with cross-functional teams to develop scalable pricing products that keep our marketplace efficient, reliable, and ready to grow. As a Sr Staff Machine Learning Engineer, you'll build a world-class pricing system that efficiently prices every offer made to Uber's delivery partners-impacting hundreds of millions of consumers and millions of merchants worldwide. What You Will Do Technical Leadership & Innovation Lead the design and implementation of advanced ML systems for courier pricing algorithms serving millions of couriers Own end-to-end ML model lifecycle from research through production deployment and continuous optimization Platform & Architecture Build scalable ML architecture and feature management systems supporting Courier Pricing and broader Marketplace teams Design experimentation frameworks enabling rapid testing of pricing algorithms using A/B, Switchback, Synthetic Control, and other experimental methodologies Establish ML engineering best practices, monitoring, and operational excellence across the organization Create platform abstractions that enable other ML engineers to iterate faster on pricing algorithms Cross-Functional Impact Collaborate with Marketplace Engineering and Science teams to productionize cutting-edge ML research Work with Platform Engineering teams to ensure ML systems meet reliability and performance standards Influence technical roadmaps across multiple teams through technical leadership and strategic thinking Team Development Mentor and grow senior ML engineers, establishing technical standards and engineering culture Lead technical discussions and architecture reviews for complex ML systems Basic Qualifications PhD in Computer Science, Machine Learning, Operations Research, or related quantitative field OR Master's degree with 12+ years of industry experience 10+ years of experience building and deploying ML models in large-scale production environments Expert-level proficiency in modern ML frameworks (TensorFlow, PyTorch) and distributed computing platforms (Spark) Deep expertise across multiple areas including: Deep Learning, Causal Inference, Reinforcement Learning, Multi-objective Optimization, and Algorithmic Game Theory Proven track record of leading complex ML projects from research through production with significant measurable business impact Strong programming skills in Python, Java, or Go with experience building production ML systems Experience with feature engineering, model serving, and ML infrastructure at scale (handling millions of predictions per second) Technical leadership experience including mentoring senior engineers and driving cross-team technical initiatives Preferred Qualifications Marketplace or two-sided platform ML experience with understanding of supply-demand dynamics and pricing mechanisms Publications or patents in applied machine learning, particularly in areas relevant to optimization, pricing, or marketplace dynamics Experience with causal inference methodologies and their application to business problems with network effects Reinforcement learning experience in production environments with long-term optimization and strategic agent considerations Technical leadership experience including mentoring senior engineers and driving cross-team technical initiatives Experience with real-time ML systems requiring low-latency inference and high-throughput model serving Background in economics, operations research, or related quantitative disciplines with application to marketplace problems For San Francisco, CA-based roles: The base salary range for this role is USD$257,000 per year - USD$285,500 per year. For Sunnyvale, CA-based roles: The base salary range for this role is USD$257,000 per year - USD$285,500 per year. For all US locations, you will be eligible to participate in Uber's bonus program, and may be offered an equity award & other types of comp. You will also be eligible for various benefits. More details can be found at the following link ************************************** Uber's mission is to reimagine the way the world moves for the better. Here, bold ideas create real-world impact, challenges drive growth, and speed fuels progress. What moves us, moves the world - let's move it forward, together. Uber is proud to be an Equal Opportunity employer. All qualified applicants will receive consideration for employment without regard to sex, gender identity, sexual orientation, race, color, religion, national origin, disability, protected Veteran status, age, or any other characteristic protected by law. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. If you have a disability or special need that requires accommodation, please let us know by completing this form. Offices continue to be central to collaboration and Uber's cultural identity. Unless formally approved to work fully remotely, Uber expects employees to spend at least half of their work time in their assigned office. For certain roles, such as those based at green-light hubs, employees are expected to be in-office for 100% of their time. Please speak with your recruiter to better understand in-office expectations for this role. #J-18808-Ljbffr

About the Role The Courier Pricing team sits within Uber's Delivery Marketplace org and plays a key role in shaping pricing across food, grocery, and other delivery verticals. We work closely with cross-functional teams to develop scalable pricing products that keep our marketplace efficient, reliable, and ready to grow. As a Sr Staff Machine Learning Engineer, you'll build a world-class pricing system that efficiently prices every offer made to Uber's delivery partners-impacting hundreds of millions of consumers and millions of merchants worldwide. What You Will Do Technical Leadership & Innovation Lead the design and implementation of advanced ML systems for courier pricing algorithms serving millions of couriers Own end-to-end ML model lifecycle from research through production deployment and continuous optimization Platform & Architecture Build scalable ML architecture and feature management systems supporting Courier Pricing and broader Marketplace teams Design experimentation frameworks enabling rapid testing of pricing algorithms using A/B, Switchback, Synthetic Control, and other experimental methodologies Establish ML engineering best practices, monitoring, and operational excellence across the organization Create platform abstractions that enable other ML engineers to iterate faster on pricing algorithms Cross-Functional Impact Collaborate with Marketplace Engineering and Science teams to productionize cutting-edge ML research Work with Platform Engineering teams to ensure ML systems meet reliability and performance standards Influence technical roadmaps across multiple teams through technical leadership and strategic thinking Team Development Mentor and grow senior ML engineers, establishing technical standards and engineering culture Lead technical discussions and architecture reviews for complex ML systems Basic Qualifications PhD in Computer Science, Machine Learning, Operations Research, or related quantitative field OR Master's degree with 12+ years of industry experience 10+ years of experience building and deploying ML models in large-scale production environments Expert-level proficiency in modern ML frameworks (TensorFlow, PyTorch) and distributed computing platforms (Spark) Deep expertise across multiple areas including: Deep Learning, Causal Inference, Reinforcement Learning, Multi-objective Optimization, and Algorithmic Game Theory Proven track record of leading complex ML projects from research through production with significant measurable business impact Strong programming skills in Python, Java, or Go with experience building production ML systems Experience with feature engineering, model serving, and ML infrastructure at scale (handling millions of predictions per second) Technical leadership experience including mentoring senior engineers and driving cross-team technical initiatives Preferred Qualifications Marketplace or two-sided platform ML experience with understanding of supply-demand dynamics and pricing mechanisms Publications or patents in applied machine learning, particularly in areas relevant to optimization, pricing, or marketplace dynamics Experience with causal inference methodologies and their application to business problems with network effects Reinforcement learning experience in production environments with long-term optimization and strategic agent considerations Technical leadership experience including mentoring senior engineers and driving cross-team technical initiatives Experience with real-time ML systems requiring low-latency inference and high-throughput model serving Background in economics, operations research, or related quantitative disciplines with application to marketplace problems For San Francisco, CA-based roles: The base salary range for this role is USD$257,000 per year - USD$285,500 per year. For Sunnyvale, CA-based roles: The base salary range for this role is USD$257,000 per year - USD$285,500 per year. For all US locations, you will be eligible to participate in Uber's bonus program, and may be offered an equity award & other types of comp. You will also be eligible for various benefits. More details can be found at the following link ************************************** Uber's mission is to reimagine the way the world moves for the better. Here, bold ideas create real-world impact, challenges drive growth, and speed fuels progress. What moves us, moves the world - let's move it forward, together. Uber is proud to be an Equal Opportunity employer. All qualified applicants will receive consideration for employment without regard to sex, gender identity, sexual orientation, race, color, religion, national origin, disability, protected Veteran status, age, or any other characteristic protected by law. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. If you have a disability or special need that requires accommodation, please let us know by completing this form. Offices continue to be central to collaboration and Uber's cultural identity. Unless formally approved to work fully remotely, Uber expects employees to spend at least half of their work time in their assigned office. For certain roles, such as those based at green-light hubs, employees are expected to be in-office for 100% of their time. Please speak with your recruiter to better understand in-office expectations for this role. #J-18808-Ljbffr

A leading transportation network company in San Francisco is seeking a Machine Learning Engineer to tackle strategic marketplace problems. The ideal candidate will shape technical roadmaps with leadership, design algorithms using large-scale data, and oversee the product lifecycle from model pipeline to implementation. This role requires a PhD in a relevant field and 4+ years of experience in machine learning. Competitive salary and bonuses included. #J-18808-Ljbffr

A leading tech company in San Francisco is seeking an experienced Machine Learning Engineer to optimize pricing systems for rides. You will collaborate with Engineers, Operations Researchers, and Economists, developing scalable systems to forecast demand and set prices based on real-time conditions. The ideal candidate holds a PhD and has at least 4 years of experience with deep learning and optimization. A competitive salary package is offered, including eligibility for bonuses and equity awards. #J-18808-Ljbffr

**About the Role** Have you ever ordered a car service on Uber, and when the ride arrives, wondered how it got to you so fast? Ever ordered food on UberEats and wondered where the driver was before receiving your order and how long it took to get to the restaurant or if your order was ready when the courier arrived? Ever wondered why your grocery delivery from Uber always has the best apple picked? If so, Uber is for you. In our Sciences division, we strive to make magic within Uber's marketplace. This requires judgment to make difficult trade-offs, blending algorithms with human resourcefulness, and the ability to build simplicity from complexity. When we get the balance right for everyone, Uber magic happens. We build systems to peer into the future to craft the most cost-efficient marketplace for matching supply and demand. We are passionate about using innovative economics, machine learning, and scalable distributed software that automates and optimizes every aspect of this intricate dance between participants of the marketplace. We are involved in every stage of the product development cycle and use data to inform product decisions, build models to power our solutions, and also develop platform tools that are used across teams with a primary focus on Mobility and Delivery. We work with millions of earners across the globe to make this magic happen and want you to join us! **About the Team** Earners (drivers and couriers) are an integral part of Uber's multi-sided marketplace. They provide the time and the means to move people and things. Importantly, they enable the connection between the physical and digital world to make the movement happen at the push of a button for everyone, everywhere. Within Uber, Earner Growth plays a critical role in earners' journey as the team is responsible for earner onboarding, activation, early life cycle, and resurrection. This presents the teams with the opportunity to shape and tailor the product experience during earners' many firsts (i.e., first time interacting on the Uber platform, choosing the earning opportunity, going online, receiving incentive offers, completing a trip, or reading the earnings summary). These firsts can be daunting. Therefore, making sure that the earner journey is great at every touch point is important to build trust with Earners, communicate Uber's value proposition, and ensure each firsts to be a great experience. **What You Will Do** + Build statistical, optimization, and machine learning models + Develop innovative new earner incentives that earners for choosing our network and optimizing Uber's new earner incentives spend + Optimize Uber's background check spend and onboarding funnel + Design recommendation engines to recommend the most relevant earning opportunities and early lifecycle content + Develop matching algorithms for driver to driver mentorship program + Model and predict earner behaviors to improve earner experience throughout the onboarding funnel + The team employs a variety of ML/AI techniques, spanning from causal ML meta learners, supervised ML, RL multi-armed bandits, gen AI LLM to deep learning embeddings to build impactful data products. + Work closely with multi-functional leads to develop technical vision, new methodological approaches, and drive team direction. + Collaborate with cross-functional teams such as product, engineering, operations, and marketing to drive ML system development end-to-end from conceptualization to final product. **Basic Qualifications** + Masters or PhD or equivalent experience in Computer Science, Machine Learning, Operations Research, Statistics, or other related quantitative fields or related field + 7 years minimum of industry experience as a Machine Learning Engineer/Research Scientist with a strong focus on deep learning and probabilistic modeling. + Proficiency in multiple object-oriented programming languages (e.g. Python, Go, Java, C++). + Experience with any of the following: Spark, Hive, Kafka, Cassandra. + Experience building and productionizing innovative end-to-end Machine Learning systems. + Experience in exploratory data analysis, statistical modeling, hypothesis testing, and experimental design. + Experience working with cross-functional teams(product, science, product ops etc). **Preferred Qualifications** + 8+ years of industry experience in machine learning, including building and deploying ML models. + Publications at industry recognized ML conferences. + Experience in modern deep learning architectures and probabilistic modeling. + Experience with optimization techniques, including reinforcement learning (RL), Bayesian methods, causal ML meta learners, gen AI LLM. + Expertise in the design and architecture of ML systems and workflows. For New York, NY-based roles: The base salary range for this role is USD$232,000 per year - USD$258,000 per year. For San Francisco, CA-based roles: The base salary range for this role is USD$232,000 per year - USD$258,000 per year. For Seattle, WA-based roles: The base salary range for this role is USD$232,000 per year - USD$258,000 per year. For Sunnyvale, CA-based roles: The base salary range for this role is USD$232,000 per year - USD$258,000 per year. For all US locations, you will be eligible to participate in Uber's bonus program, and may be offered an equity award & other types of comp. You will also be eligible for various benefits. More details can be found at the following link ************************************** Uber is proud to be an Equal Opportunity/Affirmative Action employer. All qualified applicants will receive consideration for employment without regard to sex, gender identity, sexual orientation, race, color, religion, national origin, disability, protected Veteran status, age, or any other characteristic protected by law. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. If you have a disability or special need that requires accommodation, please let us know by completing this form- ***************************************************************************************************

**About the Role** Uber is launching AV Labs to accelerate the autonomous technology ecosystem. We're building out a high-velocity team of multi-disciplinary experts to turn real-world operations into high-quality data for our autonomous partners. This team will be focused on the hardest problem in AV today: unlocking real-world, long-tail driving data. Autonomy is now a data race-and Uber has an edge: We collect rare, real-world driving data at a scale and capital efficiency no one else can match (millions of Uber trips every hour across cities, conditions, and edge cases create the data autonomy has been missing). We will build platforms that harness scale and real-world complexity to reimagine how the world moves. You will be an AI/ML engineer in AV Labs and involved in the development and implementation of the latest machine learning techniques for computer vision and perception use cases. The ideal candidate will be able to identify issues, provide solutions and implement the fixes as well as setting a high technical excellence bar in all things we do. You'll be able to collaborate with other engineers across networking, storage, compute, big data and cloud engineering, as well as with partner engineering teams which enables Uber's mission of helping people go anywhere and get anything and earn their way. **What You Will Do** + Design and deliver software and tools as part of our state-of-the-art Machine Learning platform. + Participate in developing the vision and technology roadmap for ML and Computer Vision at Uber. + Provide technical leadership, influence and partner with fellow engineers to architect, design and build scalable solutions for ML and Computer Vision technology that can stand the test of scale and availability, while reducing operational overhead. + Systems architecture design, including management of upstream and downstream dependencies. + Drive datasets to accelerate ML and Computer Vision technologies, sensor data collection, processing, labeling, indexing and building comprehensive driving scenarios. + Collaborate with platform, product and security engineering teams, and enable successful use of the latest ML techniques. + Own the craftsmanship, reliability, and scalability of your solutions. + Mentor and guide the professional and technical development of engineers on your team, and continuously improve software engineering practices. **Basic Qualifications** + Minimum 6 years of working experience in the ML/Robotics industry + Bachelor degree in computer science, computer engineering or related fields + Proficient in Python and Linux + Proficient in perception technologies + Familiar with OpenCV, TensorFlow/PyTorch + Experience in leading large initiatives **Preferred Qualifications** + Master or PhD degree in computer vision or robotics + Familiar with C++ Familiar with the Robot Operating System (ROS) For San Francisco, CA-based roles: The base salary range for this role is USD$232,000 per year - USD$258,000 per year. You will be eligible to participate in Uber's bonus program, and may be offered an equity award & other types of comp. You will also be eligible for various benefits. More details can be found at the following link ************************************** Uber is proud to be an Equal Opportunity/Affirmative Action employer. All qualified applicants will receive consideration for employment without regard to sex, gender identity, sexual orientation, race, color, religion, national origin, disability, protected Veteran status, age, or any other characteristic protected by law. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. If you have a disability or special need that requires accommodation, please let us know by completing this form- ***************************************************************************************************

**About the Role** The Consumer Incentives team is responsible for the profitability and growth trajectory of Uber's business across various verticals, including food and grocery. Our objective is to enhance the customer experience by making it more pleasant and affordable. The team addresses complex challenges in machine learning, optimization, and distributed systems to power products that serve hundreds of millions of individuals globally. ---- What You Will Do ---- In this role, you will provide ML technical leadership, help identify gaps/opportunities, and influence the direction of technical solutions to enhance incentive efficiency, while optimizing user experience across various verticals, including food and grocery. Key responsibilities include: 1. Identifying strategic technical investments to push the efficiency frontier and boost business growth. 2. Leading teams to design and implement ML/optimization solutions to meet ambitious business goals. 3. Managing end-to-end project execution, from scoping and offline evaluation to experimentation, production, and post-launch operation. 4. Collaborating with cross-functional teams, including product, operations, and science partners. ---- Basic Qualifications ---- 1. Master (or equivalent in Computer Science, Engineering, Mathematics or related field) with 6+ years of full-time ML engineering experience 2. Expertise in deep learning and optimization algorithms. 3. Experience with ML frameworks such as PyTorch and TensorFlow. 4. Experience building and productionizing innovative end-to-end Machine Learning systems. 5. Proficiency in one or more coding languages such as Python, Java, Go, or C++. 6. Strong communication skills and can work effectively with cross-functional partners. ---- Preferred Qualifications ---- 1. PhD in relevant fields (CS, EE, Math, Stats, etc.) with a focus on Machine Learning and 4+ years of experience in ML role with an emphasis on data and experiment driven model development. 2. Experience in serving and monitoring online training systems such as real time recommendation systems. 3. Experience designing and implementing novel metrics for performance evaluation. 4. Proven track record in conducting experiments and tracking models in high-complexity environments. For San Francisco, CA-based roles: The base salary range for this role is USD$232,000 per year - USD$258,000 per year. For Sunnyvale, CA-based roles: The base salary range for this role is USD$232,000 per year - USD$258,000 per year. For all US locations, you will be eligible to participate in Uber's bonus program, and may be offered an equity award & other types of comp. You will also be eligible for various benefits. More details can be found at the following link ************************************** Uber is proud to be an Equal Opportunity/Affirmative Action employer. All qualified applicants will receive consideration for employment without regard to sex, gender identity, sexual orientation, race, color, religion, national origin, disability, protected Veteran status, age, or any other characteristic protected by law. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. If you have a disability or special need that requires accommodation, please let us know by completing this form- ***************************************************************************************************

About the Role The Consumer Incentives team is responsible for the profitability and growth trajectory of Uber's business across various verticals, including food and grocery. Our objective is to enhance the customer experience by making it more pleasant and affordable. The team addresses complex challenges in machine learning, optimization, and distributed systems to power products that serve hundreds of millions of individuals globally. \-\-\-\- What You Will Do ---- In this role, you will provide ML technical leadership, help identify gaps/opportunities, and influence the direction of technical solutions to enhance incentive efficiency, while optimizing user experience across various verticals, including food and grocery. Key responsibilities include: 1. Identifying strategic technical investments to push the efficiency frontier and boost business growth. 2. Leading teams to design and implement ML/optimization solutions to meet ambitious business goals. 3. Managing end-to-end project execution, from scoping and offline evaluation to experimentation, production, and post-launch operation. 4. Collaborating with cross-functional teams, including product, operations, and science partners. \-\-\-\- Basic Qualifications ---- 1. Master (or equivalent in Computer Science, Engineering, Mathematics or related field) with 6+ years of full-time ML engineering experience 2. Expertise in deep learning and optimization algorithms. 3. Experience with ML frameworks such as PyTorch and TensorFlow. 4. Experience building and productionizing innovative end-to-end Machine Learning systems. 5. Proficiency in one or more coding languages such as Python, Java, Go, or C++. 6. Strong communication skills and can work effectively with cross-functional partners. \-\-\-\- Preferred Qualifications ---- 1. PhD in relevant fields (CS, EE, Math, Stats, etc.) with a focus on Machine Learning and 4+ years of experience in ML role with an emphasis on data and experiment driven model development. 2. Experience in serving and monitoring online training systems such as real time recommendation systems. 3. Experience designing and implementing novel metrics for performance evaluation. 4. Proven track record in conducting experiments and tracking models in high-complexity environments. For San Francisco, CA-based roles: The base salary range for this role is USD$232,000 per year - USD$258,000 per year. For Sunnyvale, CA-based roles: The base salary range for this role is USD$232,000 per year - USD$258,000 per year. For all US locations, you will be eligible to participate in Uber's bonus program, and may be offered an equity award & other types of comp. You will also be eligible for various benefits. More details can be found at the following link [****************************************************************************** Uber's mission is to reimagine the way the world moves for the better. Here, bold ideas create real-world impact, challenges drive growth, and speed fuels progress. What moves us, moves the world - let's move it forward, together. Uber is proud to be an Equal Opportunity employer. All qualified applicants will receive consideration for employment without regard to sex, gender identity, sexual orientation, race, color, religion, national origin, disability, protected Veteran status, age, or any other characteristic protected by law. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. If you have a disability or special need that requires accommodation, please let us know by completing [this form](************************************* Offices continue to be central to collaboration and Uber's cultural identity. Unless formally approved to work fully remotely, Uber expects employees to spend at least half of their work time in their assigned office. For certain roles, such as those based at green-light hubs, employees are expected to be in-office for 100% of their time. Please speak with your recruiter to better understand in-office expectations for this role.

##### ABOUT THE ROLE Applied AI at Uber builds intelligent systems that power next-generation product experiences for riders, drivers, merchants, and couriers. As a Staff AI/ML Engineer, you will operate as a full-stack technical leader across AI, backend infrastructure, and machine learning platforms - owning systems end-to-end from model development to highly reliable, large-scale distributed services that power real-time AI experiences in production. This role requires strong AI/ML and infrastructure expertise, including designing and operating distributed systems, ML platforms, and data-intensive services, alongside hands-on development of machine learning and generative AI models. You will build and scale production-grade ML infrastructure, enable rapid experimentation, and ensure reliability, observability, and cost efficiency at Uber scale. You will partner closely with platform, infra, and product teams to define foundational AI services, establish ML system abstractions, and set architectural direction for how AI capabilities are built, deployed, and operated across Uber's ecosystem. This role is ideal for engineers who operate comfortably as both AI experts and backend infrastructure leaders, setting technical direction and raising the bar for production ML systems at scale. ##### WHAT YOU'LL DO: * Build end-to-end AI products - from prototype to scalable production deployment - integrating LLMs and multimodal AI into Uber's consumer, earner, and enterprise experiences. * Implement automated evaluation systems that use LLM-as-a-judge techniques to benchmark model quality, ensure consistency, and accelerate experimentation. * Design and implement high-throughput, low-latency backend services and APIs that connect to leading AI models (e.g., OpenAI, Claude, Gemini, Mistral), ensuring production reliability, low latency, fault tolerance, and cost optimization at scale. * Lead the development of ML infrastructure for training, fine-tuning, evaluation, and deployment - including feature pipelines, model serving, offline/online consistency, and experiment management. * Own production ML systems end-to-end, including rollout strategies, monitoring, alerting, capacity planning, and on-call readiness. Establish best practices for ML systems design, including versioning, reproducibility, data validation, model lifecycle management, and safe deployment. * Collaborate across disciplines (engineering, product, design, and data science) to define user problems and translate them into AI-powered solutions. * Mentor engineers and data scientists, fostering a culture of technical excellence and cross-functional learning. ##### Basic Qualifications: * 10+ years of experience in software engineering, data science, or machine learning, including a track record of shipping production AI systems. * Deep understanding of large language models, including fine-tuning, prompt engineering, embeddings, and retrieval-augmented generation (RAG). * Strong backend and distributed systems expertise, with experience designing and operating highly available, scalable services in production. * Deep experience with ML infrastructure, including model training pipelines, online serving systems, feature stores, experiment platforms, and evaluation frameworks. * Proficiency in Python, Go, or Java, with demonstrated ability to build data- and compute-intensive backend systems. * Hands-on experience with distributed data processing systems (e.g., Spark, Flink, Ray) and workflow orchestration (e.g., Airflow or equivalent). * Ability to analyze data, run experiments, and derive insights for model and product improvement. * Excellent communication and collaboration skills across technical and non-technical teams. ##### Preferred Qualifications: * Master's or Ph.D. in Computer Science, Data Science, or related field. * Experience integrating foundation model APIs (OpenAI, Claude, Gemini, Cohere, etc.) into production-grade systems. * Proven ability to architect AI-powered backend services, optimizing for scalability, latency, and cost efficiency. * Background in LLM evaluation systems or AI agent orchestration frameworks (LangChain, Semantic Kernel, etc.). * Demonstrated success leading cross-functional projects that deliver measurable user or business impact. * Familiarity with multimodal AI (text, speech, and image models) and data-centric development workflows. * Strong understanding of model serving architectures, including online inference, batch inference, caching strategies, and GPU utilization. For San Francisco, CA-based roles: The base salary range for this role is USD$232,000 per year - USD$258,000 per year. You will be eligible to participate in Uber's bonus program, and may be offered an equity award & other types of comp. You will also be eligible for various benefits. More details can be found at the following link [****************************************************************************** Uber's mission is to reimagine the way the world moves for the better. Here, bold ideas create real-world impact, challenges drive growth, and speed fuels progress. What moves us, moves the world - let's move it forward, together. Uber is proud to be an Equal Opportunity employer. All qualified applicants will receive consideration for employment without regard to sex, gender identity, sexual orientation, race, color, religion, national origin, disability, protected Veteran status, age, or any other characteristic protected by law. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. If you have a disability or special need that requires accommodation, please let us know by completing [this form](************************************* Offices continue to be central to collaboration and Uber's cultural identity. Unless formally approved to work fully remotely, Uber expects employees to spend at least half of their work time in their assigned office. For certain roles, such as those based at green-light hubs, employees are expected to be in-office for 100% of their time. Please speak with your recruiter to better understand in-office expectations for this role.

**About the Role** The Consumer Incentives team is responsible for the profitability and growth trajectory of Uber's business across various verticals, including food and grocery. Our objective is to enhance the customer experience by making it more pleasant and affordable. The team addresses complex challenges in machine learning, optimization, and distributed systems to power products that serve hundreds of millions of individuals globally. ---- What You Will Do ---- In this role, you will provide ML technical leadership, help identify gaps/opportunities, and influence the direction of technical solutions to enhance incentive efficiency, while optimizing user experience across various verticals, including food and grocery. Key responsibilities include: 1. Identifying strategic technical investments to push the efficiency frontier and boost business growth. 2. Leading teams to design and implement ML/optimization solutions to meet ambitious business goals. 3. Managing end-to-end project execution, from scoping and offline evaluation to experimentation, production, and post-launch operation. 4. Collaborating with cross-functional teams, including product, operations, and science partners. ---- Basic Qualifications ---- 1. Master (or equivalent in Computer Science, Engineering, Mathematics or related field) with 6+ years of full-time ML engineering experience 2. Expertise in deep learning and optimization algorithms. 3. Experience with ML frameworks such as PyTorch and TensorFlow. 4. Experience building and productionizing innovative end-to-end Machine Learning systems. 5. Proficiency in one or more coding languages such as Python, Java, Go, or C++. 6. Strong communication skills and can work effectively with cross-functional partners. ---- Preferred Qualifications ---- 1. PhD in relevant fields (CS, EE, Math, Stats, etc.) with a focus on Machine Learning and 4+ years of experience in ML role with an emphasis on data and experiment driven model development. 2. Experience in serving and monitoring online training systems such as real time recommendation systems. 3. Experience designing and implementing novel metrics for performance evaluation. 4. Proven track record in conducting experiments and tracking models in high-complexity environments. For San Francisco, CA-based roles: The base salary range for this role is USD$232,000 per year - USD$258,000 per year. For Sunnyvale, CA-based roles: The base salary range for this role is USD$232,000 per year - USD$258,000 per year. For all US locations, you will be eligible to participate in Uber's bonus program, and may be offered an equity award & other types of comp. You will also be eligible for various benefits. More details can be found at the following link ************************************** Uber is proud to be an Equal Opportunity/Affirmative Action employer. All qualified applicants will receive consideration for employment without regard to sex, gender identity, sexual orientation, race, color, religion, national origin, disability, protected Veteran status, age, or any other characteristic protected by law. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. If you have a disability or special need that requires accommodation, please let us know by completing this form- ***************************************************************************************************

About the Role The role will be within the pricing and incentives domain in Uber's marketplace team. The team charter spans incentive allocation and optimization to balance the market and optimize revenue, dynamic trip pricing based on marketplace conditions. The role will provide an opportunity to work on some of the most strategic marketplace problems at Uber scale that impact Uber's global business very directly. What You Will Do: * Work with product, data science, and eng leadership to shape the technical roadmap and problem formulations for the team. * Leverage algorithmic knowledge in machine learning/optimization/statistics to design robust engineering solutions to positively impact Uber's business. * Shape the MLE role and uplevel MLE talents in the org. * Be responsible for the End to End of the product - ML model pipeline & system design, implementation, AB testing, and rollout. Work with the team to productionize the solutions at scale. Basic Qualifications: * PhD or equivalent in Computer Science, Engineering, Mathematics or related field * 4+ years full-time Machine Learning Engineering work experience in leveraging machine learning/statistics/optimization to build models in production * Collaborative and work well with, and contribute to, a team Preferred Qualifications: * Experience building algorithms with large scale data * Track record of building large-scale, highly-available systems for both batch and streaming * Deep domain expertise and are one of the recognized specialists in one or multiple areas like reinforcement learning, personalization, or deep learning. * Experience in combining observational data with experimental data for building causal models. * Experience working on large scale Machine Learning platforms For San Francisco, CA-based roles: The base salary range for this role is USD$232,000 per year - USD$258,000 per year. For Sunnyvale, CA-based roles: The base salary range for this role is USD$232,000 per year - USD$258,000 per year. For all US locations, you will be eligible to participate in Uber's bonus program, and may be offered an equity award & other types of comp. You will also be eligible for various benefits. More details can be found at the following link [****************************************************************************** Uber's mission is to reimagine the way the world moves for the better. Here, bold ideas create real-world impact, challenges drive growth, and speed fuels progress. What moves us, moves the world - let's move it forward, together. Uber is proud to be an Equal Opportunity employer. All qualified applicants will receive consideration for employment without regard to sex, gender identity, sexual orientation, race, color, religion, national origin, disability, protected Veteran status, age, or any other characteristic protected by law. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. If you have a disability or special need that requires accommodation, please let us know by completing [this form](************************************* Offices continue to be central to collaboration and Uber's cultural identity. Unless formally approved to work fully remotely, Uber expects employees to spend at least half of their work time in their assigned office. For certain roles, such as those based at green-light hubs, employees are expected to be in-office for 100% of their time. Please speak with your recruiter to better understand in-office expectations for this role.

About the Role Uber's Marketplace is at the heart of Uber's business and the Dynamic Supply Pricing (DSP) team develops the models, algorithms, signals, and large-scale distributed systems that power real-time driver pricing for billions of rides. Engineers on the team work on cutting-edge marketplace ML problems and real-time multi-objective optimizations serving 1M+ predictions/second. They regularly present $1B+ opportunities to executive stakeholders and receive close mentorship from the most senior engineers within the organization, setting you up for fast-tracked career growth and the opportunity to learn from experienced technical leaders. We are looking for exceptional ML engineers with a track record of extraordinary impact and with a passion for building large-scale systems that optimize multi-sided real-time marketplaces. In this role, you will lead the design, development, and productionization of advanced ML models and pricing algorithms, covering deep learning, causal modeling, and reinforcement learning. You will work with engineers, product managers, and scientists to set the team's technical direction and solve some of Uber's most challenging and most complex business problems in order to provide earnings opportunities for millions of drivers worldwide. What You Will Do * Drive technical strategy and roadmap ownership over a 1+ year horizon and own the implementation, including platform-level architecture decisions, executive communication and alignment, technical mentorship, and cross-team technical influence * Lead the design, development, and productionization of end-to-end ML solutions for large-scale distributed systems serving billions of trips * Develop novel pricing approaches for online marketplaces combining machine learning, algorithmic game theory, and optimization to provide earnings opportunities for millions of drivers * Work with a team of engineers, product managers, and scientists to design and deliver high-impact technical solutions to complex business problems Basic Qualifications * Ph.D., M.S. or Bachelor's degree in Computer Science, Machine Learning, or Operations Research, or equivalent technical background with exceptional demonstrated impact * 6+ years experience leading the development and deployment of ML models and optimization algorithms in large-scale production environments at top-tier ML companies (e.g. 1M+ predictions/sec or 100M+ users). Track record of delivering outstanding business impact over multiple quarters * Proficiency in programming languages such as Python, Scala, Java, or Go * Proficiency with large-scale data systems (e.g. Spark, Ray), real-time processing (e.g. Flink), and microservices architectures * Proficiency in the development, training, productionization and monitoring of ML solutions at scale, ranging from offline pipelines to online serving and MLOps * Experience in developing and deploying pricing algorithms for multi-sided real-time marketplaces with strategic agent behavior * Deep understanding of modern ML algorithms (e.g. DNNs, multi-task models, transformers) and mathematical optimization (e.g. multi-objective, LP, convex optimization) Preferred Qualifications * Experience developing multi-year technical strategies and cross-team platform architecture, and proficiency owning technical roadmap and leading complex technical projects while substantially influencing the scope and output of others * Track record of translating complex business problems into technical solutions and driving multi-functional projects across multiple teams * Excellent communication skills to lead initiatives across multiple product areas and collaborate effectively with cross-functional teams * Proficiency in reinforcement learning and causal machine learning For New York, NY-based roles: The base salary range for this role is USD$232,000 per year - USD$258,000 per year. For San Francisco, CA-based roles: The base salary range for this role is USD$232,000 per year - USD$258,000 per year. For Seattle, WA-based roles: The base salary range for this role is USD$232,000 per year - USD$258,000 per year. For Sunnyvale, CA-based roles: The base salary range for this role is USD$232,000 per year - USD$258,000 per year. For all US locations, you will be eligible to participate in Uber's bonus program, and may be offered an equity award & other types of comp. You will also be eligible for various benefits. More details can be found at the following link [****************************************************************************** Uber's mission is to reimagine the way the world moves for the better. Here, bold ideas create real-world impact, challenges drive growth, and speed fuels progress. What moves us, moves the world - let's move it forward, together. Uber is proud to be an Equal Opportunity employer. All qualified applicants will receive consideration for employment without regard to sex, gender identity, sexual orientation, race, color, religion, national origin, disability, protected Veteran status, age, or any other characteristic protected by law. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. If you have a disability or special need that requires accommodation, please let us know by completing [this form](************************************* Offices continue to be central to collaboration and Uber's cultural identity. Unless formally approved to work fully remotely, Uber expects employees to spend at least half of their work time in their assigned office. For certain roles, such as those based at green-light hubs, employees are expected to be in-office for 100% of their time. Please speak with your recruiter to better understand in-office expectations for this role.

About the Role The Ads Machine Learning (Ads ML) team at Uber is responsible for providing relevant ad recommendations to the users across the different applications within the Uber ecosystem. We focus on building a deep understanding of both user and merchant behavior to generate accurate ML signals that enhance the Ads auction system providing accurate pricing for our advertisers. Our goal is to maximize the benefits for both users and merchants within Uber's Ads distribution system. You will directly impact Uber's Ads systems by defining and executing the Ads ML roadmap, with a focus on enabling and accelerating large-scale improvements to our recommendation and auction systems. Developing relevant, robust, and observable ad recommendations is crucial to Uber's fast growing Ads Business strategy, making this a highly impactful role. \-\-\-\- What the Candidate Will Do ---- 1. Design and implement machine learning models and algorithms to optimize ad recommendations and auction mechanisms. 2. Develop and maintain scalable ML pipelines and data infrastructure to support real-time and batch processing of large-scale datasets. 3. Apply advanced statistical and machine learning techniques to generate insights and improve the effectiveness of ad targeting and delivery. 4. Collaborate with data scientists and engineers to build and refine predictive models that enhance user engagement and merchant benefits. 5. Conduct rigorous experimentation and A/B testing to validate model performance and iterate on improvements. 6. Define success metrics and develop dashboards to monitor and visualize the performance of ML models in production. 7. Work closely with cross-functional teams, including Product, Engineering, and Data Science, to translate business requirements into ML solutions. 8. Mentor and provide technical guidance to junior ML engineers and data scientists. 9. Stay up-to-date with the latest research and advancements in machine learning, recommendation systems, and ad auction techniques. \-\-\-\- Basic Qualifications ---- 01. Bachelor's degree or equivalent experience in Computer Science, Computer Engineering, Data Science, ML, Statistics, or other quantitative fields. 02. Proven experience with designing and implementing machine learning models in production environments. 03. Proficiency in using Python for developing ML models and handling large-scale data sets. 04. Solid understanding of SQL and experience using it in a production environment. 05. Strong grasp of Big Data architecture and experience with ETL frameworks and platforms. 06. Hands-on experience with building batch data pipelines using technologies like Spark or other map-reduce frameworks. 07. Expertise in experimental design and analysis, including A/B testing, exploratory data analysis, and statistical analysis. 08. Experience with data visualization tools and creating insightful dashboards. 09. Proficiency with methodologies such as sampling, statistical estimates, and descriptive statistics. 10. Ability to synthesize complex data analyses into clear and actionable insights to influence product direction. 11. Experience with recommendation systems. 12. Fast learner with a passion for solving complex problems and asking thoughtful questions to ensure effective solutions. 13. Strong communication skills to engage with technical, non-technical, and executive audiences effectively. 14. Commitment to seeking and providing timely feedback to drive continuous improvement. \-\-\-\- Preferred Qualifications ---- 01. 5 years of industry experience as an ML engineer or equivalent. 02. Expertise in building sophisticated systems and knowledge of Hadoop-related technologies such as HDFS, Kafka, Hive, and Presto. 03. Experience managing projects across large, ambiguous scopes and driving initiatives in a fast-moving, cross-functional environment. 04. Experience with enabling production-scale and maintaining large ML models. 05. Experience in one or more object-oriented programming languages (e.g. Python, Go, Java, C++). 06. Experience with REST APIs and Distributed Messaging / Kafka. 07. Familiarity with recommendation systems and modern ad auction techniques. 08. Experience with ad auctioning systems. 09. Experience with state-of-the-art deep learning techniques. 10. Advanced degree (Ph.D. or M.S.) in Data Science, ML, or related disciplines. For New York, NY-based roles: The base salary range for this role is USD$202,000 per year - USD$224,000 per year. For San Francisco, CA-based roles: The base salary range for this role is USD$202,000 per year - USD$224,000 per year. For all US locations, you will be eligible to participate in Uber's bonus program, and may be offered an equity award & other types of comp. You will also be eligible for various benefits. More details can be found at the following link [****************************************************************************** Uber's mission is to reimagine the way the world moves for the better. Here, bold ideas create real-world impact, challenges drive growth, and speed fuels progress. What moves us, moves the world - let's move it forward, together. Uber is proud to be an Equal Opportunity employer. All qualified applicants will receive consideration for employment without regard to sex, gender identity, sexual orientation, race, color, religion, national origin, disability, protected Veteran status, age, or any other characteristic protected by law. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. If you have a disability or special need that requires accommodation, please let us know by completing [this form](************************************* Offices continue to be central to collaboration and Uber's cultural identity. Unless formally approved to work fully remotely, Uber expects employees to spend at least half of their work time in their assigned office. For certain roles, such as those based at green-light hubs, employees are expected to be in-office for 100% of their time. Please speak with your recruiter to better understand in-office expectations for this role.

About the Role Have you ever ordered a car service on Uber, and when the ride arrives, wondered how it got to you so fast? Ever ordered food on UberEats and wondered where the driver was before receiving your order and how long it took to get to the restaurant or if your order was ready when the courier arrived? Ever wondered why your grocery delivery from Uber always has the best apple picked? If so, Uber is for you. In our ML and Science division, we strive to make magic within Uber's marketplace. This requires judgment to make difficult trade-offs, blending algorithms with human resourcefulness, and the ability to build simplicity from complexity. When we get the balance right for everyone, Uber magic happens. We build systems to peer into the future to craft the most cost-efficient marketplace for matching supply and demand. We are passionate about using innovative economics, machine learning, and scalable distributed software that automates and optimizes every aspect of this intricate dance between participants of the marketplace. We are involved in every stage of the product development cycle and use data to inform product decisions, build models to power our solutions, and also develop platform tools that are used across teams with a primary focus on Mobility and Delivery. We work with millions of earners across the globe to make this magic happen and want you to join us! About the Team Earners (drivers and couriers) are an integral part of Uber's multi-sided marketplace. They provide the time and the means to move people and things. Importantly, they enable the connection between the physical and digital world to make the movement happen at the push of a button for everyone, everywhere. Within Uber, Earner Growth plays a critical role in earners' journey as the team is responsible for earner onboarding, activation, early life cycle, and resurrection. This presents the teams with the opportunity to shape and tailor the product experience during earners' many firsts (i.e., first time interacting on the Uber platform, choosing the earning opportunity, going online, receiving incentive offers, completing a trip, or reading the earnings summary). These firsts can be daunting. Therefore, making sure that the earner journey is great at every touch point is important to build trust with Earners, communicate Uber's value proposition, and ensure each firsts to be a great experience. What You'll Do * Build statistical, optimization, and machine learning models * Develop innovative new earner incentives that earners for choosing our network and optimizing Uber's new earner incentives spend * Optimize Uber's background check spend and onboarding funnel * Design recommendation engines to recommend the most relevant earning opportunities and early lifecycle content * Develop matching algorithms for driver to driver mentorship program * Model and predict earner behaviors to improve earner experience throughout the onboarding funnel * The team employs a variety of ML/AI techniques, spanning from causal ML meta learners, supervised ML, RL multi-armed bandits, gen AI LLM to deep learning embeddings to build impactful data products. * Work closely with multi-functional leads to develop technical vision, new methodological approaches, and drive team direction. * Collaborate with cross-functional teams such as product, engineering, operations, and marketing to drive ML system development end-to-end from conceptualization to final product. Basic Qualifications * PhD or equivalent experience in Computer Science, Machine Learning, Operations Research, Statistics, or other related quantitative fields or related field * 4 years minimum of industry experience as a Machine Learning Engineer/Research Scientist with a strong focus on deep learning and probabilistic modeling. * Proficiency in multiple object-oriented programming languages (e.g. Python, Go, Java, C++). * Experience with any of the following: Spark, Hive, Kafka, Cassandra. * Experience building and productionizing innovative end-to-end Machine Learning systems. * Experience in exploratory data analysis, statistical modeling, hypothesis testing, and experimental design. * Experience working with cross-functional teams(product, science, product ops etc). Preferred Qualifications * 5+ years of industry experience in machine learning, including building and deploying ML models. * Publications at industry recognized ML conferences. * Experience in modern deep learning architectures and probabilistic modeling. * Experience with optimization techniques, including reinforcement learning (RL), Bayesian methods, causal ML meta learners, gen AI LLM. * Expertise in the design and architecture of ML systems and workflows. Uber's mission is to reimagine the way the world moves for the better. Here, bold ideas create real-world impact, challenges drive growth, and speed fuelds progress. What moves us, moves the world - let's move it forward, together. Offices continue to be central to collaboration and Uber's cultural identity. Unless formally approved to work fully remotely, Uber expects employees to spend at least half of their work time in their assigned office. For certain roles, such as those based at green-light hubs, employees are expected to be in-office for 100% of their time. Please speak with your recruiter to better understand in-office expectations for this role. \*Accommodations may be available based on religious and/or medical conditions, or as required by applicable law. To request an accommodation, please reach out to [accommodations@uber.com](mailto:accommodations@uber.com). For New York, NY-based roles: The base salary range for this role is USD$202,000 per year - USD$224,000 per year. For San Francisco, CA-based roles: The base salary range for this role is USD$202,000 per year - USD$224,000 per year. For Seattle, WA-based roles: The base salary range for this role is USD$202,000 per year - USD$224,000 per year. For Sunnyvale, CA-based roles: The base salary range for this role is USD$202,000 per year - USD$224,000 per year. For all US locations, you will be eligible to participate in Uber's bonus program, and may be offered an equity award & other types of comp. You will also be eligible for various benefits. More details can be found at the following link [****************************************************************************** Uber's mission is to reimagine the way the world moves for the better. Here, bold ideas create real-world impact, challenges drive growth, and speed fuels progress. What moves us, moves the world - let's move it forward, together. Uber is proud to be an Equal Opportunity employer. All qualified applicants will receive consideration for employment without regard to sex, gender identity, sexual orientation, race, color, religion, national origin, disability, protected Veteran status, age, or any other characteristic protected by law. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. If you have a disability or special need that requires accommodation, please let us know by completing [this form](************************************* Offices continue to be central to collaboration and Uber's cultural identity. Unless formally approved to work fully remotely, Uber expects employees to spend at least half of their work time in their assigned office. For certain roles, such as those based at green-light hubs, employees are expected to be in-office for 100% of their time. Please speak with your recruiter to better understand in-office expectations for this role.

**About the Role** The NOVA AI team builds the platform and AI that powers world-class support across mobile, web, and voice at global scale. We are now hiring a Senior ML Engineer to build and scale an autonomous support agent that resolves customer issues end-to-end. You'll push the state of the art in GenAI for customer service-LLM orchestration, evaluation, safety guardrails, multilingual support-while holding a very high bar for reliability and cost efficiency. We are still at an early stage and value candidates with bias for action who get creative with GenAI tools to accelerate execution and experimentation. **What the Candidate Will Need / Bonus Points** ---- What the Candidate Will Do ---- 1. Work on agent architecture: agentic planning and execution loops, long-term memory, persona/voice, knowledge routing, and policy enforcement for compliant, on-brand conversations. 2. Ship production systems that handle millions of conversations with rigorous SLOs, fallbacks, and canaries; design graceful degradation (e.g., human handoff) and safety guardrails (prompt-injection, jailbreak, PII redaction). 3. Advance retrieval & reasoning: Build next-generation retrieval and reasoning pipelines, where the agent can search across different knowledge sources, apply policy-driven tools, and call structured workflows and ensure that responses are consistently grounded. 4. Establish evals that matter: offline rubrics, simulated scenarios, safety tests, cost/latency tradeoff suites, and LLM-as-judge (with calibrated human review) wired into CI/CD and experiment platforms. 5. Drive automation at scale: partner with Product/Design/Operations on coverage, policy alignment, localization, and rollout strategy to better customer experience and reduce cost per contact. ---- Basic Qualifications ---- 1. Background in LLM-driven systems (inference optimization, prompt/program design, fine-tuning, distillation/LoRA, safety/guardrails, evals). 2. Strong software engineering in Python 3. Track record of shipping customer-facing intelligent experiences with measurable impact (A/B testing, metrics literacy). 4. Bachelor's degree (or above) in Computer Science or related field ---- Preferred Qualifications ---- 1. Agentic architectures in production (planner/executor, memory, multi-step reasoning) and RAG over complex, policy-heavy knowledge bases. 2. Experience building support automation for large consumer platforms (routing, policy codification, internal tooling, co-pilot/auto-resolve). 3. Multilingual NLU/NLG (code-switching, low-resource languages), hallucination mitigation, safety red-teaming, and privacy-by-design. 4. Practical expertise balancing speed and reliability at scale: experiment frameworks, feature flags, canary/guarded rollouts, and clear kill-switches. For Sunnyvale, CA-based roles: The base salary range for this role is USD$202,000 per year - USD$224,000 per year. You will be eligible to participate in Uber's bonus program, and may be offered an equity award & other types of comp. You will also be eligible for various benefits. More details can be found at the following link ************************************** Uber is proud to be an Equal Opportunity/Affirmative Action employer. All qualified applicants will receive consideration for employment without regard to sex, gender identity, sexual orientation, race, color, religion, national origin, disability, protected Veteran status, age, or any other characteristic protected by law. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. If you have a disability or special need that requires accommodation, please let us know by completing this form- ***************************************************************************************************

About the Role Uber's Marketplace is at the heart of Uber's business and the Dynamic Supply Pricing (DSP) team develops the models, algorithms, signals, and large-scale distributed systems that power real-time driver pricing for billions of rides. Engineers on the team work on cutting-edge marketplace ML problems and real-time multi-objective optimizations serving 1M+ predictions/second. They regularly present $1B+ opportunities to executive stakeholders and receive close mentorship from the most senior engineers within the organization, setting you up for fast-tracked career growth and the opportunity to learn from experienced technical leaders. We are looking for exceptional ML engineers with a track record of extraordinary impact and with a passion for building large-scale systems that optimize multi-sided real-time marketplaces. In this role, you will lead the design, development, and productionization of advanced ML models and pricing algorithms, covering deep learning, causal modeling, and reinforcement learning. You will work with engineers, product managers, and scientists to set the team's technical direction and solve some of Uber's most challenging and most complex business problems in order to provide earnings opportunities for millions of drivers worldwide. What You Will Do * Lead the design, development, and productionization of end-to-end ML solutions for large-scale distributed systems serving billions of trips * Develop novel pricing approaches for online marketplaces combining machine learning, algorithmic game theory, and optimization to provide earnings opportunities for millions of drivers * Collaborate with the team leads to set the team's technical direction and own its implementation, providing technical mentorship to junior engineers * Work with a team of engineers, product managers, and scientists to design and deliver high-impact technical solutions to complex business problems Basic Qualifications * Ph.D., M.S. or Bachelor's degree in Computer Science, Machine Learning, or Operations Research, or equivalent technical background with exceptional demonstrated impact * 4+ years of experience in developing and deploying machine learning models and optimization algorithms in large-scale production environments, delivering measurable business impact over multiple quarters and making significant technical contributions * Proficiency in programming languages such as Python, Scala, Java, or Go * Experience with large-scale data systems (e.g. Spark, Ray), real-time processing (e.g. Flink), and microservices architectures * Experience in the development, training, productionization and monitoring of ML solutions at scale, ranging from offline pipelines to online serving and MLOps * Deep understanding of modern ML algorithms (e.g. DNNs, multi-task models, transformers) and mathematical optimization (e.g. LP, convex optimization) Preferred Qualifications * Experience in developing and deploying pricing algorithms for multi-sided real-time marketplaces with strategic agent behavior * Experience leading complex technical projects and influencing the scope and output of others * Track record of translating ambiguous business problems into technical solutions and driving multi-functional projects * Excellent communication skills to lead initiatives and collaborate effectively with cross-functional partners * Experience in reinforcement learning and causal machine learning For New York, NY-based roles: The base salary range for this role is USD$202,000 per year - USD$224,000 per year. For San Francisco, CA-based roles: The base salary range for this role is USD$202,000 per year - USD$224,000 per year. For Seattle, WA-based roles: The base salary range for this role is USD$202,000 per year - USD$224,000 per year. For Sunnyvale, CA-based roles: The base salary range for this role is USD$202,000 per year - USD$224,000 per year. For all US locations, you will be eligible to participate in Uber's bonus program, and may be offered an equity award & other types of comp. You will also be eligible for various benefits. More details can be found at the following link [****************************************************************************** Uber's mission is to reimagine the way the world moves for the better. Here, bold ideas create real-world impact, challenges drive growth, and speed fuels progress. What moves us, moves the world - let's move it forward, together. Uber is proud to be an Equal Opportunity employer. All qualified applicants will receive consideration for employment without regard to sex, gender identity, sexual orientation, race, color, religion, national origin, disability, protected Veteran status, age, or any other characteristic protected by law. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. If you have a disability or special need that requires accommodation, please let us know by completing [this form](************************************* Offices continue to be central to collaboration and Uber's cultural identity. Unless formally approved to work fully remotely, Uber expects employees to spend at least half of their work time in their assigned office. For certain roles, such as those based at green-light hubs, employees are expected to be in-office for 100% of their time. Please speak with your recruiter to better understand in-office expectations for this role.

**About the Role** You will be an ML engineer doing Autonomous Vehicles related research. An ideal candidate will drive foundational and applied research that advances the capabilities of next-generation autonomous systems. **What the Candidate Will Need / Bonus Points** ---- What the Candidate Will Do ---- 1. Work on cutting edge research problems in the Autonomous Vehicles domain. 2. Publish papers in ML conferences. 3. Collaborate with the engineering team to productionize research ideas. ---- Basic Qualifications ---- + Ph.D., M.S. or Bachelor's degree in Computer Vision, Computer Science, Machine Learning, or equivalent technical background with exceptional demonstrated impact + 2+ years of experience in developing and deploying machine learning models + Proficiency in programming languages such as Python, Scala, Java, or Go + Publications in top ML conferences. + Deep understanding in computer vision and large language models. + Proficient in prototyping research ideas using popular deep learning frameworks. ---- Preferred Qualifications ---- 1. Experience with Autonomous Vehicles related research. For Sunnyvale, CA-based roles: The base salary range for this role is USD$171,000 per year - USD$190,000 per year. You will be eligible to participate in Uber's bonus program, and may be offered an equity award & other types of comp. You will also be eligible for various benefits. More details can be found at the following link ************************************** Uber is proud to be an Equal Opportunity/Affirmative Action employer. All qualified applicants will receive consideration for employment without regard to sex, gender identity, sexual orientation, race, color, religion, national origin, disability, protected Veteran status, age, or any other characteristic protected by law. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. If you have a disability or special need that requires accommodation, please let us know by completing this form- ***************************************************************************************************