Careers

Are you excited by the idea of inventing new experiences on the most visited shopping page - amazon.com? Can you imagine saving millions of shoppers' time worldwide by presenting them with compelling products, services, and offers on Amazon homepage and product detail pages? Are you looking forward to solving challenging problems that blend business, scientific, and engineering disciplines? We work with billions of products and measure our impact in $'00 millions. Join us, be part of the shopping revolution, make history, and earn bragging rights! Key job responsibilities - Utilize artificial intelligence (includes Generative AI), causal inference, and creative problem-solving skills to improve one of the most significant ecommerce algorithms that impacts millions of shoppers and sellers in the planet. - Partner closely with engineers to put your research and ideas into production on Amazon.com. - Leverage your science expertise to research and deliver novel solutions to explore emerging problem spaces, and create or organize knowledge around them. - Publish papers and file patents to contribute to the machine learning community. - Present ideas to senior leadership (Sr. Managers and above) and mentor Applied Scientists and Engineers with an interest in artificial intelligence. - Provide scientific consultation and influence teams beyond your immediate group, such as, Personalization, Media content teams, and Ads. About the team Buying Experience (BuyX) connects shoppers worldwide with the best product and offer evaluation experiences. Our Homepage guides customers to their next discovery—whether restocking essentials or exploring new Amazon services—through personalized, engaging content. On the Detail Page, we showcase products with tailored experiences across geographies and intents. Our team drives innovation through advanced algorithms, insightful product comparisons, dynamic content policies, and scalable architecture, ensuring every customer makes confident, informed decisions with each visit. We are a team of Scientists, Economists, and Engineers, working together to realize this mission. We operate in a diverse space that includes modeling of customer purchase behavior, advanced simulation and experimentation. We employ a variety of AI/ML, and econometric techniques.

The Artificial General Intelligence (AGI) team is looking for a passionate, talented, and inventive Senior Applied Scientist with a strong deep learning background, to lead the development of industry-leading technology with multimodal systems. Key job responsibilities As a Senior Applied Scientist with the AGI team, you will lead the development of novel algorithms and modeling techniques to advance the state of the art with multimodal systems. Your work will directly impact our customers in the form of products and services that make use of vision and language technology. You will leverage Amazon’s heterogeneous data sources and large-scale computing resources to accelerate development with multimodal Large Language Models (LLMs) and Generative Artificial Intelligence (GenAI) in Computer Vision. About the team The AGI team has a mission to push the envelope with multimodal LLMs and GenAI in Computer Vision, in order to provide the best-possible experience for our customers.

We are seeking a talented applied researcher to join the Whole Page Planning and Optimization (WPPO) Science team in Search. The latest data from Business Insider shows that almost 50% of online shoppers visit Amazon first. The Search WPPO Science team is responsible for developing reinforcement learning systems for the next generation Amazon shopping experience and delivering it to millions of customers. We believe that shopping on Amazon should be simple, delightful, and full of WOW moments for EVERYONE, whether you are technically savvy or new to online shopping. As an Applied Scientist, you will be working closely with a team of applied scientists and engineers to build systems that shape the future of Amazon's shopping experience by automatically generating relevant content and building a whole page experience that is coherent, dynamic, and interesting. You will improve ranking and optimization in our algorithm. You will participate in driving features from idea to deployment, and your work will directly impact millions of customers. You are going to love this job because you will: * Apply state-of-the-art Machine Learning (ML) algorithms, including Deep Learning and Reinforcement Learning, to improve hundreds of millions of customers’ shopping experience. * Have measurable business impact using A/B testing. * Work in a dynamic team that provides continuous opportunities for learning and growth. * Work with leaders in the field of machine learning. Joining this team, you’ll experience the benefits of working in a dynamic, entrepreneurial environment, while leveraging the resources of Amazon.com (AMZN), one of the world's leading internet companies. We provide a highly customer-centric, team-oriented environment. A successful candidate will have a solid research background in machine learning and reinforcement learning algorithms, customer obsession, great communication skills, and the motivation to achieve results in a fast-paced environment.

Are you passionate about transforming the digital reading and publishing landscape? The Kindle Books Team is at the forefront of revolutionizing the publishing and reading experience for millions worldwide. We are seeking innovative Applied Scientists to join us at the forefront of the digital transformation in the publishing industry. Our team is dedicated to enhancing the book publishing and reading experience using cutting-edge AI technology. We strive to streamline the publishing lifecycle, improve digital reading, and empower book publishers through innovative AI tools and solutions to grow their business on Amazon. We are building a holistic team focused on leveraging advances in AI to improve the Reading experience for Kindle customers, and the Publishing experience for book content creators and distributors; and this role is specifically for an Applied Scientist who will focus on making publishers lives easier through AI. Key job responsibilities - Inspect AI initiatives across Amazon to identify how these can be applied and scaled to book publishers or publishing workflows. - Participate in team design, scoping and prioritization discussions. You must be able to map a business goal to a scientific problem, and map business metrics to technical metrics. - Spearhead the design and implementation of new features and algorithms based on thorough research and collaboration with cross-functional teams. - You have expertise in one of the applied science disciplines, such as machine learning, natural language processing, computer vision, Deep learning - You are able to use reasonable assumptions, data, and customer requirements to solve problems. - You initiate the design, development, execution, and implementation of smaller components with input and guidance from team members. - You work with SDEs to deliver solutions into production to benefit customers or an area of the business. - You assume responsibility for the code in your components. You write secure, stable, testable, maintainable code with minimal defects. - You understand basic data structures, algorithms, model evaluation techniques, performance, and optimality tradeoffs. - You follow engineering and scientific method best practices. You get your designs, models, and code reviewed. You test your code and models thoroughly - You participate in team design, scoping and prioritization discussions. You are able to map a business goal to a scientific problem and map business metrics to technical metrics. - You invent, refine and develop your solutions to ensure they are meeting customer needs and team goals. You keep current with research trends in your area of expertise and scrutinize your results. - Experience in mentoring junior scientists A day in the life You will be working with a group of talented scientists on researching algorithm and running experiments to test solutions to improve our experience. This will involve collaboration with partner teams including engineering, PMs, data annotators, and other scientists to discuss data quality, model development and productionizing the same. You will mentor other scientists, review and guide their work, help develop roadmaps for the team.

Amazon Search JP builds features powering product search on the Amazon JP shopping site and expands the innovations to world wide. As an Applied Scientist on this growing team, you will take on a key role in improving the NLP and ranking capabilities of the Amazon product search service. Our ultimate goal is to help customers find the products they are searching for, and discover new products they would be interested in. We do so by developing NLP components that cover a wide range of languages and systems. As an Applied Scientist for Search JP, you will design, implement and deliver search features on Amazon site, helping millions of customers every day to find quickly what they are looking for. You will propose innovation in NLP and IR to build ML models trained on terabytes of product and traffic data, which are evaluated using both offline metrics as well as online metrics from A/B testing. You will then integrate these models into the production search engine that serves customers, closing the loop through data, modeling, application, and customer feedback. The chosen approaches for model architecture will balance business-defined performance metrics with the needs of millisecond response times. Key job responsibilities - Designing and implementing new features and machine learned models, including the application of state-of-art deep learning to solve search matching, ranking and Search suggestion problems. - Analyzing data and metrics relevant to the search experiences. - Working with teams worldwide on global projects. Your benefits include: - Working on a high-impact, high-visibility product, with your work improving the experience of millions of customers - The opportunity to use (and innovate) state-of-the-art ML methods to solve real-world problems with tangible customer impact - Being part of a growing team where you can influence the team's mission, direction, and how we achieve our goals

Amazon's Optimal Inventory Health (OIH) org in Supply Chain Optimization (SCOT) group is looking for a Principal Applied Scientist to optimize one of the most complex eCommerce systems in the world. The Optimal Inventory Health (OIH) drives long-term cash flow (LTFCF) growth by determining optimal inventory dispositions under uncertainties in demand, pricing, and supply across Amazon’s 21 marketplaces global network. OIH is in the unique position within SCOT to drive the joint optimization across supply chain and marketing across the levers of Markdowns, Removals, Outlet, Deals, Sponsored Ads, and Paid Search etc. Our systems deliver hundreds of million dollars saving to Amazon each year. The Principal Applied Scientist will lead the transformation from optimization-based model to Machine Learning/Reinforcement learning based decision-making models to optimize across inventory disposition channels and deliver best experience to Amazon customers through those levers. The role requires multidisciplinary skill sets across Reinforcement learning, Deep Learning Prediction, and Causal Inference et cetera. Academic and/or practical background in Transformer Architecture and Deep Reinforcement Learning are particularly relevant for this position. This position requires drive and self-motivation, superior analytical thinking, data-driven disposition, application of technical knowledge to a business context, effective collaboration with fellow scientists, software development engineers, and product managers, effective communication of technical designs to technical and non-technical audiences, and close partnership with many stakeholders from operations, finance, IT, and business leadership. Key job responsibilities - Seek to understand in depth the end to end value chain of eCommerce across supply chain and marketing and identify areas of opportunities to grow our business using science solutions. - Lead science strategy and roadmap in OIH space - Drive alignment across organizations to achieve business goals - Lead/guide scientists and engineers across teams to develop, test, launch and improve of science models designed to optimize inventory value and customer experience. - Be responsible for communicating our innovations to the broader internal & external scientific community and business leadership. - Mentor and guide the applied scientists in our organization and hold us to a high standard of technical rigor and excellence in ML. A day in the life - You will engage with distinguished scientists and Senior Principal scientists across organizations to shape the vision of the eCommerce decision systems across supply chain and marketing. - Our machine learning infrastructure built by talented engineering team (feature stores, template based ML pipelines and integration with experiment and production systems) will enable you to quickly prototype and iterate your innovative ideas. - You will collaborate with talented product managers and software engineers to build the end-to-end systems. - You will work with stakeholders across retail, supply chain, finance etc. to understand the business operation process and bottlenecks and build solution to provide the best experience to Amazon customers through automated OIH actions. About the team Supply Chain Optimization Technology (SCOT) is the core of the Amazon eCommerce business, which leverage science models and systems to automate the decisions and operations of the most complex supply chain in the world. Optimal Inventory Health (OIH) maximize the inventory value in Amazon through all the levers across traffic, marketing, pricing and reverse logistics.

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 India Consumer Businesses. 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

Amazon’s Last Mile Team is looking for a passionate individual with strong optimization and analytical skills to join its Last Mile Science team in the endeavor of designing and improving the most complex planning of delivery network in the world. Last Mile builds global solutions that enable Amazon to attract an elastic supply of drivers, companies, and assets needed to deliver Amazon's and other shippers' volumes at the lowest cost and with the best customer delivery experience. Last Mile Science team owns the core decision models in the space of jurisdiction planning, delivery channel and modes network design, capacity planning for on the road and at delivery stations, routing inputs estimation and optimization. Our research has direct impact on customer experience, driver and station associate experience, Delivery Service Partner (DSP)’s success and the sustainable growth of Amazon. Optimizing the last mile delivery requires deep understanding of transportation, supply chain management, pricing strategies and forecasting. Only through innovative and strategic thinking, we will make the right capital investments in technology, assets and infrastructures that allows for long-term success. Our team members have an opportunity to be on the forefront of supply chain thought leadership by working on some of the most difficult problems in the industry with some of the best product managers, scientists, and software engineers in the industry. Key job responsibilities Candidates will be responsible for developing solutions to better manage and optimize delivery capacity in the last mile network. The successful candidate should have solid research experience in one or more technical areas of Operations Research or Machine Learning. These positions will focus on identifying and analyzing opportunities to improve existing algorithms and also on optimizing the system policies across the management of external delivery service providers and internal planning strategies. They require superior logical thinkers who are able to quickly approach large ambiguous problems, turn high-level business requirements into mathematical models, identify the right solution approach, and contribute to the software development for production systems. To support their proposals, candidates should be able to independently mine and analyze data, and be able to use any necessary programming and statistical analysis software to do so. Successful candidates must thrive in fast-paced environments, which encourage collaborative and creative problem solving, be able to measure and estimate risks, constructively critique peer research, and align research focuses with the Amazon's strategic needs. As a senior scientist, you will also help coach/mentor junior scientists in the team.

The Bedrock AI Data Team in Amazon Web Services (AWS) is looking for a Language Engineer to collaborate in developing solutions for natural language data collections. This position is an opportunity to apply your expertise in a challenging but supportive environment. We are open to hiring candidates to work out of one of the following locations: The mission of the Bedrock AI Data Team is to engineer the datasets critical to the success of AWS’s Bedrock services. From human evaluations to Responsible AI safeguards to Retrieval-Augmented Generation and beyond, these products make Generative AI enterprise-ready and safe for users, impacting millions of people every day. We are a group of language engineers, linguists, data scientists, data engineers, and program managers, and we partner closely with the science, engineering, and product teams. We are customer obsessed and committed to delivering results with the highest quality and integrity. As a Language Engineer, you will start by diving deep into a couple of critical projects for Bedrock services to drive these projects forward. You will collaborate with fellow language engineers, program managers, as well as stakeholders in science, engineering, and product teams to understand the role data plays in developing models that meet customer needs. You will analyze, follow, and improve processes for collecting and annotating LLM inputs and outputs, assessing data quality, and automating where appropriate. You will then expand your scope by using the principles of data-centric AI to understand the role our data plays with regard to model performance specifically, as well as the larger ML pipeline. You will apply state-of-the-art Generative AI techniques to analyze how well our data represents human language and run experiments to gauge downstream interactions. You will work collaboratively with other language engineers and scientists to design and implement principled strategies for data optimization. Locations include Seattle, WA, USA | Santa Clara, CA, USA | New York City, NY, USA Key job responsibilities - Source, validate, and deliver high-quality language artifacts and linguistic data - Collaborate with stakeholders to design data collection and development efforts - Oversee the progress and quality of several data collection and annotation projects at a time - Advocate for strict adherence to data collection guidelines and quality thresholds - Extend existing data collection, annotation, and quality assurance efforts to support feature and language expansion - Innovate on data collection methodologies, guidelines, quality metrics to support new requests - Automate repetitive workflows and improve existing processes A day in the life The Bedrock AI Data Team at AWS is responsible for delivering high-quality annotated data and a variety of language artifacts to ensure the best performance of different AWS LLM services. These Generative AI services enable customers to readily add intelligence to their business operations and AI applications to drive positive outcomes. About the team AWS Utility Computing (UC) provides product innovations — from foundational services such as Amazon’s Simple Storage Service (S3) and Amazon Elastic Compute Cloud (EC2), to consistently released new product innovations that continue to set AWS’s services and features apart in the industry. As a member of the UC organization, you’ll support the development and management of Compute, Database, Storage, Internet of Things (Iot), Platform, and Productivity Apps services in AWS, including support for customers who require specialized security solutions for their cloud services. 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. Hybrid Work We value innovation and recognize this sometimes requires uninterrupted time to focus on a build. We also value in-person collaboration and time spent face-to-face. Our team affords employees options to work in the office every day or in a flexible, hybrid work model near one of our U.S. Amazon offices.

We are seeking a Principal Applied Scientist to join our industry-leading team developing cutting-edge technologies in multi-robot planning and control. This is a unique opportunity to play a pivotal role in enabling fleets of autonomous mobile robots to operate safely and efficiently around humans in dynamic real-world environments. In this position, you will lead projects to push the boundaries of collaborative autonomy - getting teams of robots to cooperate and coordinate to get work done. You will develop and deploy new planning, coordination and control methods for our next generation of mobile robots. Your solutions will allow packs of robots to navigate warehouses transporting goods, performing services, and taking over dangerous dull dirty tasks - all while safely sharing space with people. This opportunity offers the chance to have broad impact by enabling robots to take on new roles that will transform how we work. You will collaborate with brilliant colleagues in a culture that values ingenuity, teamwork and making an impact. Come join our mission to pioneer the future of automation! About the team The Movement Science team studies algorithms for efficient motion planning and coordination of Amazon's mobile robots. Our aim is to improve the efficiency of robot movement and to enable adaptation to new operating conditions. We focus on two key requirements of movement: preserving liveness and working at scale. We are driven by system-level problems, where a new algorithm can unlock a new solution design, fix a significant shortcoming, guarantee performance under varying conditions, or improve how complex tradeoffs are made. As a science team, we take on projects which require cutting-edge research, a longer time-horizon, or carry significant risk.