Careers

The Selling Partner Experience (SPX) organization strives to make Amazon the best place for Selling Partners to do business. The SPX Science team is building an AI-powered conversational assistant to transform the Selling Partner experience. The Selling Assistant is a trusted partner and a seasoned advisor that’s always available to enable our partners to thrive in Amazon’s stores. It takes away the cognitive load of selling on Amazon by providing a single interface to handle a diverse set of selling needs. The assistant always stays by the seller's side, talks to them in their language, enables them to capitalize on opportunities, and helps them accomplish their business goals with ease. It is powered by the cutting edge of Generative AI, going beyond a typical chatbot to provide a powerful, personalized experience to sellers running real businesses, large and small. Do you want to join an innovative team of scientists, engineers, product and program managers who use state-of-the-art Generative AI and Machine Learning technologies to help Amazon create a delightful Selling Partner experience? Do you want to build solutions to real business problems by automatically understanding and addressing sellers’ challenges, needs and opportunities? Are you excited by the prospect of contributing to one of Amazon’s most strategic Generative AI initiatives? If yes, then you may be a great fit to join the Selling Partner Experience Science team (SPeXSci). Key job responsibilities - Use state-of-the-art Machine Learning and Generative AI techniques to create the next generation of the tools that empower Amazon's Selling Partners to succeed. - Design, develop and deploy highly innovative models to interact with Sellers and delight them with solutions. - Work closely with teams of scientists and software engineers to drive real-time model implementations and deliver novel and highly impactful features. - Establish scalable, efficient, automated processes for large scale data analyses, model benchmarking, model validation and model implementation. - Research and implement novel machine learning and statistical approaches. - Participate in strategic initiatives to employ the most recent advances in ML in a fast-paced, experimental environment. About the team Selling Partner Experience Science (SPeXSci) is a growing team of scientists, engineers and product leaders engaged in the research and development of the next generation of ML-driven technology to empower Amazon's Selling Partners to succeed. We draw from many science domains, from Natural Language Processing to Computer Vision to Optimization to Economics, to create solutions that seamlessly and automatically engage with Sellers, solve their problems, and help them grow. We are focused on building seller facing AI-powered tools using the latest science advancements to empower sellers to drive the growth of their business. We strive to radically simplify the seller experience, lowering the cognitive burden of selling on Amazon by making it easy to accomplish critical tasks such as launching new products, understanding and complying with Amazon’s policies and taking actions to grow their business.

Amazon is one of the most popular sites in the US. Our product search engine, one of the most heavily used services in the world, indexes billions of products and serves hundreds of millions of customers world-wide. Within Amazon Search, the Data Science team brings expertise in constrained optimization, modeling data, and experimental methods. We partner with internal and external teams to bring create pioneering new insights, develop new measurement and testing methodologies, and hone optimization strategies. We ensure Search's systems, models, and teams properly optimizing over trade-offs in the function of the search experience. In addition to working with partners, we incubate new modeling techniques, and perform 'front line recon' on potential new models and tools. We are looking for a Senior Economist to independently leverage petabyte scale data, seek out opportunities, and deliver models, metrics, or insights that creates wins for customers. Key job responsibilities Measure / Quantify / Expand - Design, size, and analyze field experiments at scale. - Apply econometric or statistical knowledge to improve Amazon Search (using machine learning techniques is a plus) - Retrieve, synthesize, and present critical data in a format that is immediately useful to answering specific questions or improving system performance. - Analyze historical data to identify trends and support decision making. Explore / Enlighten - Formalize assumptions about how Amazon Search is expected to work. - Given anomalies, whether anecdotal or identified automatically, deep dive to explain why they happen, and identify fixes. Decide / Recommend - Build decision-making models and propose solution for the business problem you defined - Analyze A/B tests and extract understanding of customer behavioral responses - Conduct written and verbal presentation to share insights and recommendations to audiences of varying levels of technical sophistication. - Utilize code (python or another object oriented language) for data analyzing and modeling algorithm About the team The mission of the Search Data Science team is to build a world class shopping experience that delights customers. We focus on the long term and big picture, ensuring that the search page is balancing strategic trade-offs. We bring to this effort expertise in constrained optimization, causal inference, and marketplace equilibrium effects. We build systems, metrics, and mechanisms to ensure that product decisions are scientifically sound. We develop models to estimate the downstream dollar value of the quality of the experience. We spend time on evaluating experiments to develop durable learnings.

The Alexa Smart Home team is focused on making Alexa the user interface for the home. From the simplest voice commands (turn on the lights, turn down the heat) to use cases spanning home security, home entertainment, and the home environment; we are evolving Alexa into an intelligent, indispensable companion that automates daily routines, simplifies interaction with appliances and electronics, and alerts when something unusual is detected. You can be part of a team delivering features that are highly anticipated by media and well received by our customers. As a Sr. Data Scientist, you will work with other scientists and software developers to design and build the next generation of Smart Home voice control using the latest Large Language Models (LLM's). And, you will have the satisfaction of working on a product your friends and family can relate to, and want to use every day. Key job responsibilities - Develop new inference and training techniques to improve the performance of LLMs for Smart Home control and automation - Develop robust techniques for synthetic data generation for training large models and maintaining model generalization - Mentoring junior scientists to improve their skills, knowledge, and ability to contribute to team projects About the team We are a team of Scientists, Machine Learning Engineers, and Software Developers that work together to make Alexa more insightful and proactive through ambient intelligence, with features like Alexa Hunches that automatically control Smart Home devices. We are interdisciplinary and we act like it. We ask each other questions and value our different perspectives.

The Alexa Smart Home team is focused on making Alexa the user interface for the home. From the simplest voice commands (turn on the lights, turn down the heat) to use cases spanning home security, home entertainment, and the home environment; we are evolving Alexa into an intelligent, indispensable companion that automates daily routines, simplifies interaction with appliances and electronics, and alerts when something unusual is detected. You can be part of a team delivering features that are highly anticipated by media and well received by our customers. As an Applied Scientist, you will work with other scientists and software developers to design and build the next generation of Smart Home voice control using the latest Large Language Models (LLM's). And, you will have the satisfaction of working on a product your friends and family can relate to, and want to use every day. Key job responsibilities - Develop new inference and training techniques to improve the performance of LLMs for Smart Home control and Automation - Develop robust techniques for synthetic data generation for training large models and maintaining model generalization - Mentoring junior scientists to improve their skills, knowledge, and their ability to get things done About the team We are a team of Scientists, Machine Learning Engineers, and Software Developers that work together to make Alexa more insightful and proactive through ambient intelligence, with features like Alexa Hunches that automatically control Smart Home devices. We are interdisciplinary and we act like it. We ask each other questions and value our different perspectives.

Do you want to help shape the future of Amazon's physical retail presence? The Location Strategy and Analytics team is looking for an Applied Scientist to join us in developing cutting-edge forecasting models, optimization models and analytical tools to support critical real estate and store planning decisions for Amazon's worldwide grocery business, including Whole Foods Market. Our team is responsible for developing sophisticated forecasting models and tools to support Real Estate and Topology analysts on important decisions regarding our stores - including new store openings, relocations, closures, remodels, design, new formats, and more. We leverage advanced data science techniques to build models for store sales forecasting, sales transfer effects, macrospace optimization, store network optimization, and store network diffusion planning. As an Applied Scientist on our team, you will apply your technical and analytical skills to tackle complex business problems and develop innovative solutions to improve our forecasting and decision-making capabilities. You will collaborate with a diverse team of scientists, economists, and business partners to identify opportunities, develop hypotheses, and translate analytical insights into actionable recommendations. Key job responsibilities - Design and implement advanced forecasting models and machine learning solutions to predict store performance and optimize our retail network - Analyze large datasets to uncover insights and patterns related to store performance, customer behavior, and market dynamics - Develop end-to-end solutions, tools and frameworks to scale our ML model development and data analysis. - Leverage Generative AI techniques to enhance user interaction with our solutions and improve overall user experience - Present research findings and recommendations to scientists, business leaders, and executives - Collaborate with cross-functional teams to drive adoption of models and insights - Stay current on latest developments in relevant fields and propose innovative approaches About the team We are a team of scientists passionate about leveraging data and advanced analytics to drive strategic decisions for Amazon's physical retail business. Our work directly impacts Amazon's worldwide grocery store growth and development strategy. We foster a collaborative environment where team members are encouraged to think creatively, challenge assumptions, and pursue novel approaches to solving complex problems. Our team is at the forefront of applying cutting-edge techniques, including Generative AI, to improve our forecasting models and enhance the usability of our scientific solutions.

The Amazon Artificial General Intelligence (AGI) Personalization team is looking for a passionate, highly skilled and inventive Applied Scientist with strong machine learning background to build state-of-the-art ML systems for personalizing large-scale, high-quality conversational assistant systems. As a Applied Scientist, you will play a critical role in driving the development of personalization techniques enabling conversational systems, in particular those based on large language models, information retrieval, recommender systems and knowledge graph, to be tailored to customer needs. You will handle Amazon-scale use cases with significant impact on our customers' experiences. Key job responsibilities - Use deep learning, ML and NLP techniques to create scalable solutions for creation and development of language model centric solutions for building personalized assistant systems based on a rich set of structured and unstructured contextual signals - Innovate new methods for contextual knowledge extraction and information retrieval, using language models in combination with other learning techniques, that allows effective grounding in context providers when considering memory, compute, latency and quality - Research in advanced customer understanding and behavior modeling techniques - Collaborate with cross-functional teams of scientists, engineers, and product managers to identify and solve complex problems in personal knowledge aggregation, processing, modeling, and verification - Design and execute experiments to evaluate the performance of state-of-the-art algorithms and models, and iterate quickly to improve results - Think Big on conversational assistant system personalization over a multi-year horizon, and identify new opportunities to apply these technologies to solve real-world problems - Communicate results and insights to both technical and non-technical audiences, including through presentations and written reports About the team The AGI Personalization org uses various contextual signals to personalize Large Language Model output for our customers while maintaining privacy and security of customer data. We work across multiple Amazon products, including Alexa, to enhance the user experience by bringing more personal context and relevance to customer interactions.

Do you want to join an innovative team of scientists who use deep learning, natural language processing, large language models to help Amazon provide the best seller experience across the entire Seller life cycle, including recruitment, growth, support and provide the best customer and seller experience by automatically mitigating risk? Do you want to build advanced algorithmic systems that help manage the trust and safety of millions of customer interactions every day? Are you excited by the prospect of analyzing and modeling terabytes of data and creating state-of-the-art algorithms to solve real world problems? Are you excited by the opportunity to leverage GenAI and innovate on top of the state-of-the-art large language models to improve customer and seller experience? Do you like to build end-to-end business solutions and directly impact the profitability of the company? Do you like to innovate and simplify processes? If yes, then you may be a great fit to join the Machine Learning Accelerator team in the Amazon Selling Partner Services (SPS) group. Key job responsibilities The scope of an Applied Scientist II in the SPS Machine Learning Accelerator (MLA) team is to research and prototype Machine Learning applications that solve strategic business problems across SPS domains. Additionally, the scientist collaborates with project leaders, engineers and business partners to design and implement solutions at scale. The scientist focuses on components of large-scale projects, systems and products and can work independently and with the team to deliver successful solutions with medium to large business impact. The scientist helps our team evolve by actively participating in discussions, team planning, and by staying current on the latest techniques arising from both the scientist community in SPS, the larger Amazon-wide community, and beyond. The scientist develops and introduces tools and practices that streamline the work of the team, and he mentors junior team members and participates in hiring.

Amazon launched the Generative AI Innovation Center (GenAIIC) in June 2023 to help AWS customers accelerate the use of generative AI to solve business and operational problems and promote innovation in their organization. This is a team of strategists, data scientists, engineers, and solution architects working step-by-step with customers to build bespoke solutions that harness the power of generative AI. (https://press.aboutamazon.com/2023/6/aws-announces- generative-ai-innovation-center). We’re looking for Data Scientists to use generative AI and other techniques to design, evangelize, and implement state-of-the-art solutions for never-before-solved problems. You will work directly with customers and innovate in a fast-paced organization that contributes to game-changing projects and technologies. You will design and run experiments, research new algorithms, and find new ways of optimizing risk, profitability, and customer experience. As an early-in-career joiner, you will initially join our A2C (Associate to Consultant) program for intensive training on AWS technology and delivery approach. Emirati nationality is required. Key job responsibilities As a Data Scientist, you will - Collaborate with AI/ML scientists, engineers, and architects to Research, design, develop, and evaluate cutting-edge generative AI algorithms to address real-world challenges - Interact with customers directly to understand the business problem, help and aid them in implementation of generative AI solutions, deliver briefing and deep dive sessions to customers and guide customer on adoption patterns and paths to production - Create and deliver best practice recommendations, tutorials, blog posts, sample code, and presentations adapted to technical, business, and executive stakeholder - Provide customer and market feedback to Product and Engineering teams to help define product direction About the team The team helps customers imagine and scope the use cases that will create the greatest value for their businesses, select and train or fine tune the right models, define paths to navigate technical or business challenges, develop proof-of-concepts, and make plans for launching solutions at scale. The Generative AI Innovation Center team provides guidance on best practices for applying generative AI responsibly and cost efficiently. Diverse Experiences AWS values diverse experiences. Even if you do not meet all of the 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 (gender diversity) 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.

Job Description Are you interested in applying your strong quantitative analysis and big data skills to world-changing problems? Are you interested in driving the development of methods, models and systems for capacity planning, transportation and fulfillment network? If so, then this is the job for you. Our team is responsible for creating core analytics tech capabilities, platforms development and data engineering. We develop scalable analytics applications and research modeling to optimize operation processes. We standardize and optimize data sources and visualization efforts across geographies, builds up and maintains the online BI services and data mart. You will work with professional software development managers, data engineers, scientists, business intelligence engineers and product managers using rigorous quantitative approaches to ensure high quality data tech products for our customers around the world, including India, Australia, Brazil, Mexico, Singapore and Middle East. Amazon is growing rapidly and because we are driven by faster delivery to customers, a more efficient supply chain network, and lower cost of operations, our main focus is in the development of strategic models and automation tools fed by our massive amounts of available data. You will be responsible for building these models/tools that improve the economics of Amazon’s worldwide fulfillment networks in emerging countries as Amazon increases the speed and decreases the cost to deliver products to customers. You will identify and evaluate opportunities to reduce variable costs by improving fulfillment center processes, transportation operations and scheduling, and the execution to operational plans. You will also improve the efficiency of capital investment by helping the fulfillment centers to improve storage utilization and the effective use of automation. Finally, you will help create the metrics to quantify improvements to the fulfillment costs (e.g., transportation and labor costs) resulting from the application of these optimization models and tools. Major responsibilities include: · Translating business questions and concerns into specific analytical questions that can be answered with available data using BI tools; produce the required data when it is not available. · Apply Statistical and Machine Learning methods to specific business problems and data. · Create global standard metrics across regions and perform benchmark analysis. · Ensure data quality throughout all stages of acquisition and processing, including such areas as data sourcing/collection, ground truth generation, normalization, transformation, cross-lingual alignment/mapping, etc. · Communicate proposals and results in a clear manner backed by data and coupled with actionable conclusions to drive business decisions. · Collaborate with colleagues from multidisciplinary science, engineering and business backgrounds. · Develop efficient data querying and modeling infrastructure. · Manage your own process. Prioritize and execute on high impact projects, triage external requests, and ensure to deliver projects in time. · Utilizing code (Python, R, Scala, etc.) for analyzing data and building statistical models.

Come build the future of entertainment with us. Are you interested in helping shape the future of movies and television? Do you want to help 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 from Originals and Exclusive content to exciting live sports events. We also offer our members the opportunity to subscribe to add-on channels which they can cancel at any time 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 240 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 We are seeking an exceptional Applied Scientist to join our Prime Video Sports tech team in Israel. Our team is dedicated to developing state-of-the-art science to allow for personalizing the customers’ experience and customers to seamlessly find any live event in our selection. You will have the opportunity to work on innovative, large-scale projects that push the boundaries of what's possible in sports content delivery and engagement. Your expertise will be crucial in tackling complex challenges such as temporal information retrieval, leveraging Generative AI and Large Language Models (LLMs), and building state-of-the-art recommender systems. Key job responsibilities We are looking for an Applied Scientist with domain expertise in Personalization, Information Retrieval, and Recommender Systems, or general ML to lead the development of new algorithms and end-to-end solutions. As part of our team of applied scientists and software development engineers, you will be responsible for researching, designing, developing, and deploying algorithms into production pipelines. Your role will involve working with cutting-edge technologies such as Gen AI/LLMs to enhance content discovery and search capabilities. You'll also tackle unique challenges like temporal information retrieval to improve real-time sports content recommendations. As a technologist, you will drive the publication of original work in top-tier conferences in Machine Learning and Information Retrieval. We expect you to thrive in ambiguous situations, demonstrating outstanding analytical abilities and comfort in collaborating with cross-functional teams and systems. The ideal candidate is a self-starter with the ability to learn and adapt quickly in our fast-paced environment. About the team We are the Prime Video Sports team. In September 2018 Prime Video launched its first full-scale live streaming experience to world-wide Prime customers with NFL Thursday Night Football. That was just the start. Now Amazon has exclusive broadcasting rights to major leagues like NFL Thursday Night Football, Tennis major like Roland-Garros and English Premium League to list few and are broadcasting live events across 30+ sports world-wide. Prime Video is expanding not just the breadth of live content that it offers, but the depth of the experience. This is a transformative opportunity, the chance to be at the vanguard of a program that will revolutionize Prime Video, and the live streaming experience of customers everywhere.