Careers

Do you want to join an innovative team of scientists who use machine learning and statistical techniques to create state-of-the-art solutions for providing better value to Amazon’s customers? Do you want to build and deploy advanced algorithmic systems that help optimize millions of transactions every day? Are you excited by the prospect of analyzing and modeling terabytes of data to solve real world problems? Do you like to own end-to-end business problems/metrics and directly impact the profitability of the company? Do you like to innovate and simplify? If yes, then you may be a great fit to join the Machine Learning and Data Sciences team for FinAuto. If you have an entrepreneurial spirit, know how to deliver, love to work with data, are deeply technical, highly innovative and long for the opportunity to build solutions to challenging problems that directly impact the company's bottom-line, we want to talk to you. Major responsibilities - Use machine learning and analytical techniques to create scalable solutions for business problems - Analyze and extract relevant information from large amounts of Amazon’s historical business data to help automate and optimize key processes - Design, development, evaluate and deploy innovative and highly scalable models for predictive learning - Research and implement novel machine learning and statistical approaches - Work closely with software engineering teams to drive real-time model implementations and new feature creations - Work closely with business owners and operations staff to optimize various business operations - Establish scalable, efficient, automated processes for large scale data analyses, model development, model validation and model implementation - Mentor other scientists and engineers in the use of ML techniques Key job responsibilities Use machine learning and analytical techniques to create scalable solutions for business problems Analyze and extract relevant information from large amounts of Amazon’s historical business data to help automate and optimize key processes Design, develop, evaluate and deploy, innovative and highly scalable ML models Work closely with software engineering teams to drive real-time model implementations Work closely with business partners to identify problems and propose machine learning solutions Establish scalable, efficient, automated processes for large scale data analyses, model development, model validation and model maintenance Work proactively with engineering teams and product managers to evangelize new algorithms and drive the implementation of large-scale complex ML models in production Leading projects and mentoring other scientists, engineers in the use of ML techniques About the team The FinAuto TFAW(theft, fraud, abuse, waste) team is part of FGBS Org and focuses on building applications utilizing machine learning models to identify and prevent theft, fraud, abusive and wasteful(TFAW) financial transactions across Amazon. Our mission is to prevent every single TFAW transaction. As a Machine Learning Scientist in the team, you will be driving the TFAW Sciences roadmap, conduct research to develop state-of-the-art solutions through a combination of data mining, statistical and machine learning techniques, and coordinate with Engineering team to put these models into production. You will need to collaborate effectively with internal stakeholders, cross-functional teams to solve problems, create operational efficiencies, and deliver successfully against high organizational standards.

Do you want to work on Reinforcement Learning (RL) post-training of frontier Large Language Models (LLMs) to revolutionize customer service? Come join the world class researchers and academics in the AWS AI endeavor, and develop the science that powers countless new businesses in cloud computing! AWS, the world-leading provider of cloud services. Our customers bring problems that will give Applied Scientists like you endless opportunities to see your research have a positive and immediate impact in the world. You will have the opportunity to partner with technology and business teams to solve real-world problems, have access to virtually endless data and computational resources, and to world-class engineers and developers that can help bring your ideas into the world. As part of the team, we expect that you will develop innovative solutions to hard problems, and publish your findings at peer reviewed conferences and journals. The scientific topics you are going to work on include, but are not limited to: LLM post-training to improve capabilities particularly for instruction following, reasoning over long context, and tool use, etc. About the team Why AWS Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that’s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses. Inclusive Team Culture Here at AWS, it’s in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences, inspire us to never stop embracing our uniqueness. Work/Life Balance We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve in the cloud. Mentorship and Career Growth We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional. Diverse Experiences Amazon values diverse experiences. Even if you do not meet all of the preferred qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying.

Join the next revolution in robotics at Amazon's Frontier AI & Robotics team, where you'll work alongside world-renowned AI pioneers to push the boundaries of what's possible in robotic intelligence. As a Member of Technical Staff, you'll be at the forefront of developing breakthrough foundation models that enable robots to perceive, understand, and interact with the world in unprecedented ways. You'll drive independent research initiatives in areas such as perception, manipulation, science understanding, locomotion, manipulation, sim2real transfer, multi-modal foundation models and multi-task robot learning, designing novel frameworks that bridge the gap between state-of-the-art research and real-world deployment at Amazon scale. In this role, you'll balance innovative technical exploration with practical implementation, collaborating with platform teams to ensure your models and algorithms perform robustly in dynamic real-world environments. You'll have access to Amazon's vast computational resources, enabling you to tackle ambitious problems in areas like very large multi-modal robotic foundation models and efficient, promptable model architectures that can scale across diverse robotic applications. Key job responsibilities - Drive independent research initiatives across the robotics stack, including robotics foundation models, focusing on breakthrough approaches in perception, and manipulation, for example open-vocabulary panoptic scene understanding, scaling up multi-modal LLMs, sim2real/real2sim techniques, end-to-end vision-language-action models, efficient model inference, video tokenization - Design and implement novel deep learning architectures that push the boundaries of what robots can understand and accomplish - Lead full-stack robotics projects from conceptualization through deployment, taking a system-level approach that integrates hardware considerations with algorithmic development, ensuring robust performance in production environments - Collaborate with platform and hardware teams to ensure seamless integration across the entire robotics stack, optimizing and scaling models for real-world applications - Contribute to the team's technical strategy and help shape our approach to next-generation robotics challenges A day in the life - Design and implement novel foundation model architectures and innovative systems and algorithms, leveraging our extensive infrastructure to prototype and evaluate at scale - Collaborate with our world-class research team to solve complex technical challenges - Lead technical initiatives from conception to deployment, working closely with robotics engineers to integrate your solutions into production systems - Participate in technical discussions and brainstorming sessions with team leaders and fellow scientists - Leverage our massive compute cluster and extensive robotics infrastructure to rapidly prototype and validate new ideas - Transform theoretical insights into practical solutions that can handle the complexities of real-world robotics applications About the team At Frontier AI & Robotics, we're not just advancing robotics – we're reimagining it from the ground up. Our team is building the future of intelligent robotics through innovative foundation models and end-to-end learned systems. We tackle some of the most challenging problems in AI and robotics, from developing sophisticated perception systems to creating adaptive manipulation strategies that work in complex, real-world scenarios. What sets us apart is our unique combination of ambitious research vision and practical impact. We leverage Amazon's massive computational infrastructure and rich real-world datasets to train and deploy state-of-the-art foundation models. Our work spans the full spectrum of robotics intelligence – from multimodal perception using images, videos, and sensor data, to sophisticated manipulation strategies that can handle diverse real-world scenarios. We're building systems that don't just work in the lab, but scale to meet the demands of Amazon's global operations. Join us if you're excited about pushing the boundaries of what's possible in robotics, working with world-class researchers, and seeing your innovations deployed at unprecedented scale.

Help us build the software stack underneath Frontier AI & Robotics: the layer between hardware and the AI policies running on it. You’ll work end-to-end across the stack, from bringing up sensors and actuators at the HW/SW boundary, to hardening the multi-process runtime that ties them together, to shipping the framework changes that let the rest of the team move faster. This is a generalist role with a real systems edge. We need someone equally at home down at the sensor and OS boundary (drivers, IPC, real-time behavior, profiling) and up in robotics application code (most of it Python). You’ll spend stretches of a few days to a few weeks each on things like bringing up a new sensor at the protocol layer, chasing a flaky USB camera at the kernel boundary, generalizing the camera stack, cutting perception latency, porting code onto edge compute, or chasing a DDS/ROS 2 performance regression. You’ll work with sharp, motivated engineers across hardware, ML research, controls, and ops on continuously changing problems at the frontier of AI and robotics. The role rewards engineers who communicate clearly, invest in cross-team relationships, and ship. Key job responsibilities - Bring up and integrate sensors, actuators, and edge compute across diverse robotics hardware platforms. - Build and improve the multi-process Python and ROS 2 runtime: process management, IPC, observability, lifecycle. - Diagnose and fix bottlenecks across the stack: middleware performance (DDS, ROS 2), perception pipeline latency, edge inference throughput, system-level resource contention. - Generalize one-off solutions into reusable infrastructure (camera stacks, telemetry pipelines, edge deployment tooling) that scales across hardware platforms and use cases. - Port code onto the constrained edge-compute platforms our robots run. Make it work, then make it work well. - Identify gaps in the team’s velocity, whether that’s a missing piece of infrastructure or a fragile sensor that nobody has time to fix, and close them. - Make proper tradeoffs between prototyping and production software. About the team At Frontier AI & Robotics, we're not just advancing robotics – we're reimagining it from the ground up. Our team is building the future of intelligent robotics through frontier foundation models and end-to-end learned systems. We tackle some of the most challenging problems in AI and robotics, from developing sophisticated perception systems to creating adaptive manipulation strategies that work in complex, real-world scenarios. What sets us apart is our unique combination of ambitious research vision and practical impact. We leverage Amazon's massive computational infrastructure and rich real-world datasets to train and deploy state-of-the-art foundation models. Our work spans the full spectrum of robotics intelligence – from multimodal perception using images, videos, and sensor data, to sophisticated manipulation strategies that can handle diverse real-world scenarios. We're building systems that don't just work in the lab, but scale to meet the demands of Amazon's global operations. Join us if you're excited about pushing the boundaries of what's possible in robotics, working with world-class researchers, and seeing your innovations deployed at unprecedented scale.

We're looking for an Applied Scientist to develop computer vision and machine learning models that keep Amazon's workforce safe. Your research and models will be deployed across hundreds of operations facilities globally, helping to reduce safety incidents for over 1.5 million people. You'll join a team where science meets real-world impact. You'll design and train models for tasks like activity recognition, anomaly detection, object detection, and risk prediction using video, image, and sensor data from Amazon's operational environments. You'll work closely with software engineers to take your models from experimentation through production deployment at scale. If you're excited about applying advanced ML research to a problem that genuinely improves people's lives, and you thrive in an environment where your work ships to production, not just to a paper, this is the role for you. Key job responsibilities - Design, develop, and deploy computer vision and machine learning models for workplace safety applications (e.g., activity recognition, anomaly detection, pose estimation, object detection) - Develop and iterate on model architectures using deep learning frameworks, running experiments on large-scale video, image, and sensor datasets - Collaborate with software engineers to productionize models - optimizing for inference latency, accuracy, and reliability in edge and cloud environments - Analyze operational data to identify patterns and signals indicating safety risks, and translate findings into actionable model improvements - Stay current with the latest research in computer vision, deep learning, and related fields, and evaluate applicability to safety use cases - Communicate findings and technical approaches clearly to both technical and non-technical stakeholders through documents, presentations, and design reviews - Contribute to the team's scientific culture through code reviews, knowledge sharing, and mentorship About the team Amazon's Workplace Health & Safety (WHS) organization is responsible for keeping over 1.5 million employees safe across our global retail operations. Within WHS, our technology team builds the science and engineering capabilities that power Amazon's safety strategy at scale. We're a cross-functional group of applied scientists, software engineers, data engineers, and technical program managers developing computer vision systems, generative AI applications, sensor and IoT solutions, and analytics platforms - all aimed at reducing workplace injuries. As an applied scientist here, you'll partner directly with engineers who build the production infrastructure for your models, and with safety domain experts who ground your work in real operational needs. Our culture values scientific rigor, fast iteration, and shipping models that create measurable safety outcomes.

At Amazon Robotics, we design advanced robotic systems capable of intelligent perception, learning, and action alongside humans, at massive scale. Our mission is to deploy robots that increase productivity and efficiency across Amazon fulfillment centers while operating safely and robustly in complex, contact-rich environments. We are seeking an Applied Scientist to develop manipulation controllers for robotic systems operating in contact-rich, uncertain environments. In this role, you will design force-aware control strategies grounded in impedance/admittance frameworks and augment them with data-driven policy learning to achieve robust, adaptive manipulation behaviors. You will combine physics-based modeling, control-theoretic design, and machine learning to build manipulation capabilities that generalize across objects, tasks, and operational conditions. You will collaborate closely with experts in perception, machine learning, motion planning, controls, and software engineering to deliver solutions that perform reliably on real hardware at production scale. As part of this role, you will study and extend relevant academic and industry research in robot learning and manipulation, prototype and validate learned policies in simulation and on hardware, and transition successful approaches into production systems. Successful candidates demonstrate strong intuition for physical systems, experience applying ML to robotics problems, and the ability to reason about failure modes, edge cases, and deployment constraints in contact-rich manipulation. Clear communication, hands-on experimentation, and a bias toward practical impact are essential. Key job responsibilities - Research, design, implement, and evaluate machine learning–based manipulation policies for contact-rich tasks, integrating learning with feedback control, estimation, and motion planning. - Develop learning frameworks that leverage simulation, real-world data, and hybrid physics- and data-driven models to enable robust agency interaction, grasping, insertion, and object handling. - Design and execute experiments in simulation and on hardware to train, validate, and stress-test learned manipulation policies under real-world variability and uncertainty. - Collaborate with software engineering teams to deliver scalable, real-time, and maintainable implementations of learning-based manipulation algorithms in production robotic systems. - Partner with cross-functional teams across perception, hardware, systems engineering, science, and operations to transition learned policies from research prototypes to reliable, production-ready capabilities across Amazon Robotics platforms. A day in the life Amazon offers a full range of benefits that support you and eligible family members, including domestic partners and their children. Benefits can vary by location, the number of regularly scheduled hours you work, length of employment, and job status such as seasonal or temporary employment. The benefits that generally apply to regular, full-time employees include: 1. Medical, Dental, and Vision Coverage 2. Maternity and Parental Leave Options 3. Paid Time Off (PTO) 4. 401(k) Plan If you are not sure that every qualification on the list above describes you exactly, we'd still love to hear from you! At Amazon, we value people with unique backgrounds, experiences, and skillsets. If you’re passionate about this role and want to make an impact on a global scale, please apply!

Do you have proven analytical capabilities to identify business opportunities, develop predictive models and optimization algorithms to help us build state of the art Support organization? At Amazon, we are working to be the most customer-centric company on earth. To get there, we need exceptionally talented, bright, and driven people. We set big goals and are looking for people who can help us reach and exceed them. Amazon Web Services (AWS) is one of the world’s most comprehensive and broadly adopted cloud platform, offering over 200 fully featured services from data centers globally. Amazon Web Services, Inc. provides services for broad range of applications including compute, storage, databases, networking, analytics, machine learning and artificial intelligence (AI), Internet of Things (IoT), security, and application development, deployment, and management. AWS Support's Capacity Planning team is looking for a strong, talented Data Scientist to model contact and volume forecasting, discovering insights and identifying opportunities through the use of statistics, machine learning, and combinatorial optimization problems to drive business and operational improvements. You are passionate about building solutions that will help drive a more efficient operations network and optimize cost. In this role, you will partner with data engineering, tooling team, operations, training, workforce management and finance teams, driving optimization and prediction solutions across the network influencing the long-term strategy of the business. We are looking for an experienced and motivated Data Scientist with proven abilities to build and manage modeling projects, forecasting solutions, identify data requirements, build methodology and tools that are statistically grounded. You are an expert in the areas of data science, forecasting, optimization, machine learning and statistics, and is comfortable facilitating ideation and working from concept through execution. You are customer obsessed, innovative, independent, results-oriented and enjoys working in a fast-paced growing organization. An interest in operations, process improvement is helpful. The ability to embrace this ambiguity and work with a highly distributed team of experts is critical. While this is a small team, there is opportunity to own globally impactful work and grow your career in technical, programmatic or people leadership. You will likely to work in Python or R, building forecasting, predictive and optimization models. Your problem solving ability, knowledge of data models and ability to drive results through ambiguity are more important to us. About the team About Us Diverse Experiences AWS values diverse experiences. Even if you do not meet all of the preferred qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying. Why AWS? Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that’s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses. Inclusive Team Culture Here at AWS, it’s in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon conferences, inspire us to never stop embracing our uniqueness. Mentorship & Career Growth We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional. Work/Life Balance We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve in the cloud.

If you have ever bought or sold anything on Amazon, you have touched Amazon Marketplace. Amazon’s Marketplace business is one of the largest in the world. We are now in 23 countries. We are growing fast, with customers in many more countries. Amazon’s platform is the engine that powers Amazon’s Marketplace businesses, and Sellers rely on this platform and our support to start selling on Amazon and to grow their business. Amazon Marketplace enables millions of Sellers worldwide to list hundreds of millions of products and manage orders for inventory across dozens of different categories and languages. While working with millions of Sellers worldwide, we constantly strive to improve the selection for Customers and the capabilities of our platform for Sellers. The Seller Fulfillment Services (SFS) team is looking for a motivated and innovative Applied Scientist with strong analytical skills and practical experience to join our science team. As a key member of the SFS science team, you will provide expertise that helps accelerate the business. You will build science solutions that will help us to provide our customers with the largest selection of merchants at the lowest, and the most reliable delivery service regardless of the seller. You will research, design and improve on the models that will impact Amazon’s customer directly. You will be working in a highly collaborative environment partnering with various science, product management, engineering, operations, finance, business intelligence and analytics teams to develop science models to solve business problems. You will need to understand the business requirements and translate them into complex analytical outputs. You will design tests to explain performance of the models from impact on customer and cost perspective. You will create ML models to capture features impacting performance. You should be comfortable building prototypes, testing and improving them given the feedback from the real time data. You should be able to present your model and findings to a various range of stakeholders. Looking for candidate with expertise in the areas of machine learning, operations research, and statistics. With expertise in applying theoretical models in an applied environment relying heavily on the latest advances in machine learning, optimization, stochastic modeling, and engineering. The candidate will be expected to work on numerous aspects, such as feature engineering, modeling, probabilistic modeling, hyper-parameter tuning, scalable inference methods and latent variable models. Challenges will involve dealing with very large data sets and requirements on throughput. Key job responsibilities - Design, implement, test, deploy, and maintain innovative science solutions to accelerate our business. - Create experiments and prototype implementations of new learning algorithms and prediction techniques - Collaborate with scientists, engineers, product managers, and stakeholders to design and implement software solutions for science problems - Use best practices to ensure a high standard of quality for all of the team deliverables

Come build the future of entertainment with us. Are you interested in shaping the future of movies and television? Do you want to define the next generation of how and what Amazon customers are watching? Prime Video is a premium streaming service that offers customers a vast collection of TV shows and movies - all with the ease of finding what they love to watch in one place. We offer customers thousands of popular movies and TV shows including Amazon Originals and exclusive licensed content to exciting live sports events. We also offer our members the opportunity to subscribe to add-on channels which they can cancel at anytime and to rent or buy new release movies and TV box sets on the Prime Video Store. Prime Video is a fast-paced, growth business - available in over 200 countries and territories worldwide. The team works in a dynamic environment where innovating on behalf of our customers is at the heart of everything we do. If this sounds exciting to you, please read on. The Observability and Triage team is looking for an Applied Scientist for our London office experienced in generative AI and large models. This is a wide impact role working with development teams across the UK, India, and the US. This greenfield project will deliver features that reduce the operational load for internal Prime Video builders and for this, you will develop AI-driven solutions that automatically detect anomalies, identify root causes, recommend resolution paths and take action for operational incidents. We consume petabytes of data daily across multiple metric, log and data based events and you would be experimenting on how to shape the future through this data. You will have strong technical ability, excellent teamwork and communication skills, and a strong motivation to deliver customer value from your research. Our position offers opportunities to grow your technical and non-technical skills and make a global impact. Key job responsibilities - Design and develop machine learning and generative AI systems for automated incident triage, root cause analysis, and resolution recommendation at scale - Rapidly prototype and evaluate hypotheses in a high-ambiguity environment, leveraging both quantitative experimentation and domain expertise in operational systems - Build evaluation frameworks (including LLM-as-a-Judge approaches) to measure model accuracy across triage accuracy and root cause prediction - Collaborate with software engineering teams to integrate ML models into production observability systems serving hundreds of development teams - Communicate results and insights to both technical and non-technical audiences, including through publications, presentations, and written reports A day in the life On a typical day, you analyse patterns across thousands of operational incidents to improve an automated triage model, then design an experiment to test whether a new Generative-AI based approach better identifies root causes for complex multi-service incidents. Your internal customers are Prime Video development teams who rely on your solutions to reduce the time and effort spent responding to operational events. You will collaborate closely with software engineers, and operational stakeholders across the world to ensure your research translates into production systems that measurably remove customer impact. About the team Our team builds AI-powered observability and triage solutions for Prime Video development teams, consuming petabytes of data daily to automatically detect, diagnose, and recommend resolutions for operational incidents.

Prime Video is a first-stop entertainment destination offering customers a vast collection of premium programming in one app available across thousands of devices. Prime members can customize their viewing experience and find their favorite movies, series, documentaries, and live sports – including Amazon MGM Studios-produced series and movies; licensed fan favorites; and programming from Prime Video subscriptions such as Apple TV+, HBO Max, Peacock, Crunchyroll and MGM+. All customers, regardless of whether they have a Prime membership or not, can rent or buy titles via the Prime Video Store, and can enjoy even more content for free with ads. Are you interested in shaping the future of entertainment? Prime Video's technology teams are creating best-in-class digital video experience. As a Prime Video team member, you’ll have end-to-end ownership of the product, user experience, design, and technology required to deliver state-of-the-art experiences for our customers. You’ll get to work on projects that are fast-paced, challenging, and varied. You’ll also be able to experiment with new possibilities, take risks, and collaborate with remarkable people. We’ll look for you to bring your diverse perspectives, ideas, and skill-sets to make Prime Video even better for our customers. With global opportunities for talented technologists, you can decide where a career Prime Video Tech takes you! We are looking for an Applied Science Manager who will take care of the Content Understanding for Prime Video. Content Understanding team helps Prime Video "see" and "understand" what's actually happening inside its videos - the characters, scenes, dialogue, events, and visual elements. We build the systems that analyze video content so that we can build customer experiences on top of our work. This manager will also lead a team of scientists and engineers who are building the next generation of video understanding and search for Prime Video. You will own the strategy, execution, and delivery of systems that help machines watch, describe, and find content across the largest streaming catalog in the world. Key job responsibilities As an Applied Science Manager, you will: - Define and drive the technical direction and roadmap across our "understanding" and "search" workstreams — making sure our work connects to Prime Video's broader goals around content intelligence. - Lead and grow a high-performing team of scientists and engineers, building a culture of scientific excellence, customer focus, and reliable delivery. - Partner with teams across Prime Video (personalization, search etc) to understand what they need from us, shape our outputs to be reliable building blocks for their products, and drive adoption. - Own delivery end-to-end — from early research and experimentation all the way through launching production systems that run at the scale of Prime Video's full catalog. - Define and track success metrics for quality, reliability, and real-world impact on downstream products, continuously raising the bar on what "good" looks like. - Manage ambiguity across a broad set of workstreams, make clear prioritization decisions, and communicate trade-offs effectively to senior leadership. About the team The Prime Video - Content Localization, Understanding and Enrichment team's mission is to deeply understand content to automate & scale existing solutions, and launch new experiences across Prime Video while accelerating science outputs & forward-investing in science. This manager will lead Content Understanding that defines content at a fundamental scene-level by generating & maintaining a comprehensive set of Content Understanding attributes which are leveraged across Prime Video for their varied use-cases; ranging from content moderation to metadata generation, ad placement identification, etc.