Careers

** This position is open to all candidates in Palo Alto, CA, Seattle, WA, NYC and Arlington, VA ** Amazon Ads Response Prediction team is your choice, if you want to join a highly motivated, collaborative, and fun-loving team with a strong entrepreneurial spirit and bias for action. We are seeking an experienced and motivated Machine Learning Applied Scientist who loves to innovate at the intersection of customer experience, deep learning, and high-scale machine-learning systems. Amazon Advertising operates at the intersection of eCommerce and advertising, and is investing heavily in building a world-class advertising business. We are defining and delivering a collection of self-service performance advertising products that drive discovery and sales. Our products are strategically important to our Retail and Marketplace businesses driving long-term growth. We deliver billions of ad impressions and millions of clicks daily and are breaking fresh ground to create world-class products to improve both shopper and advertiser experience. With a broad mandate to experiment and innovate, we grow at an unprecedented rate with a seemingly endless range of new opportunities. We are looking for a talented Machine Learning Applied Scientist for our Amazon Ads Response Prediction team to grow the business. We are providing advanced real-time machine learning services to connect shoppers with right ads on all platforms and surfaces worldwide. Through the deep understanding of both shoppers and products, we help shoppers discover new products they love, be the most efficient way for advertisers to meet their customers, and helps Amazon continuously innovate on behalf of all customers. Key job responsibilities As a Machine Learning Applied Scientist, you will: * Conduct deep data analysis to derive insights to the business, and identify gaps and new opportunities * Develop scalable and effective machine-learning models and optimization strategies to solve business problems * Run regular A/B experiments, gather data, and perform statistical analysis * Work closely with software engineers to deliver end-to-end solutions into production * Improve the scalability, efficiency and automation of large-scale data analytics, model training, deployment and serving * Conduct research on new machine-learning modeling to optimize all aspects of Sponsored Products business About the team We are pioneers in applying advanced machine learning and generative AI algorithms in Sponsored Products business. We empower every customer with a customized discovery experiences from back-end optimization (such as customized response prediction models) to front-end CX innovation (such as widgets), to help shoppers feel understood and shop efficiently on and off Amazon.

We are building GenAI based shopping assistant for Amazon. We reimage Amazon Search with an interactive conversational experience that helps you find answers to product questions, perform product comparisons, receive personalized product suggestions, and so much more, to easily find the perfect product for your needs. We’re looking for the best and brightest across Amazon to help us realize and deliver this vision to our customers right away. This will be a once in a generation transformation for Search, just like the Mosaic browser made the Internet easier to engage with three decades ago. If you missed the 90s—WWW, Mosaic, and the founding of Amazon and Google—you don’t want to miss this opportunity.

Are you interested in big data, machine learning, and product recommendations? If so, the Amazon Interests team might be the right place for you. We are a team in a fast-paced organization with a huge impact on hundreds of millions of customers. We innovate at the intersection of customer experience, deep learning, and high-scale machine-learning systems. We are looking for Applied Scientists who love big data, and are capable of inventing and applying Machine Learning, Natural Language Processing, Image processing, Data Mining, Classification and Clustering techniques to solve real world problems and build novel customer facing innovations on Amazon. Our applied scientists work closely with software engineers to put algorithms into practice. They also work in partnership with teams across Amazon to create enormous benefits for our customers. As a member of the Amazon Interest team, you will be working on identifying customers unique hobbies and interests, like running, biking, gardening, etc. and build an alternate structure to existing product catalog around these interests. You would then use this structured data to create new immersive shopping experiences that customers would love. You would be expected to move fast, have good judgment on what is and what is not worth exploring, create simple and scalable solutions and identify correct problem sets. You will be surrounded by thought-leaders in the Personalization space who are patent-leaders within Amazon. You will keep the team up-to date with latest academic research in relevant fields. Key job responsibilities - 3+ years of building machine learning models for business application experience - PhD, or Master's degree and 4+ years of applied research experience - Experience programming in Java, C++, Python or related language - Experience with neural deep learning methods and machine learning A day in the life You are an Applied Scientist with an interest in machine learning, data science, search, or recommendation systems. You have great problem solving skills. You love keeping abreast of the latest technology and use it to help you innovate. You have strong leadership qualities, great judgment, clear communication skills, and a track record of delivering great products. You enjoy working hard, having fun, and making history! About the team Our team has the autonomy to decide where we can have the most impact and get down to experimenting. We love metrics and the fast pace. We analyze data to uncover potential opportunities, generate hypotheses, and test them. We refuse to accept constraints, internal or external, and have a strong bias for action. We imagine, build prototypes, validate ideas, and launch follow-up experiments from the successful ones. About our organization Consider the following problem: every day, millions of customers with unique interests and needs come to Amazon looking for products out of a catalog of over a billion items. Not only do we need to decide what content would be most helpful to customers, we also need to present it in an inspiring manner. The Personalization organization within Amazon is responsible for the secret sauce that not only made Amazon the industry pioneer in building recommender systems at scale, but is also continuing to help raise the bar for building delightful and highly personalized shopping experiences.

When customers search for products on the Amazon website, they often see brand advertisements displayed right below the search bar. These ads are part of the Sponsored Brands (SB) program. Our team, the SB Search and Relevance team, works on solving challenges to retrieve the most relevant ads for a customer's search query. A customer's search query is typically a short, free-form text consisting of just a few words. Our algorithm needs to understand the customer's underlying intention from this limited information. At the same time, each advertisement consists of various elements like text descriptions, images, videos, and more. Our algorithm also needs to comprehend the content of these ads and identify the most relevant one from the large pool of ad candidates. As Amazon's advertising business is growing rapidly, we are looking for experienced applied scientists. As an Applied Scientist on this team, you will: Build deep learning models to improve our search relevance for online advertising. - Apply deep learning and natural language processing to improve information retrieval and relevance. - Design and run A/B experiments. Evaluate the impact of your optimizations and communicate your results to various business stakeholders. - Optimize deep learning inference latency by utilizing methods like knowledge distillation. - Work with software development engineers and write code to bring models into production. Impact and Career Growth - You will invent new experiences and influence customer-facing shopping experiences to help suppliers grow their retail business and the auction dynamics that leverage native advertising; this is your opportunity to work within the fastest-growing businesses across all of Amazon! - Define a long-term science vision for our advertising business, driven fundamentally from our customers' needs, translating that direction into specific plans for research and applied scientists, as well as engineering and product teams. - This role combines science leadership, organizational ability, technical strength, product focus, and business understanding. Team video https://youtu.be/zD_6Lzw8raE

Are you fascinated by the power of Large Language Models (LLM) and applying Generative AI to solve complex challenges within one of Amazon's most significant businesses? Amazon Selection and Catalog Systems (ASCS) builds the systems that host and run the world’s largest e-Commerce products catalog - it powers the online buying experience for customers worldwide so they can find, discover and buy anything they want. Amazon’s customers rely on the completeness, consistency and correctness of Amazon's product data to make well-informed purchase decisions. Improving the quality of product data is a continuous process. It requires data driven decisions on what product data changes simplify and improve the Customers’ experience. Amazon Selection and Catalog Systems (ASCS) is seeking an Applied Scientist II for developing Generative AI and Large Language Models (LLM) that can help generate richer and expanded product information. You will be a part of a team consisting of experienced Applied Scientists working on a new set of initiatives, building models and delivering them into the Amazon production ecosystem. Your efforts will build a robust ensemble of LLM artifacts and ML systems that can achieve high precision and recall, and scale to new marketplaces and languages. This problem is challenging due to sheer scale (billions of products in the catalog), diversity (products ranging from electronics to groceries to instant video across multiple languages) and multitude of input sources (millions of sellers contributing product data with different quality). We are looking for an experienced Scientist who can develop best in class solutions. Your primary customers are Amazon shoppers who would thank you for correct product information in our catalogs across countries and languages. The ideal Applied Scientist candidate has deep expertise in one or several of the following fields: Web search, Applied/Theoretical Machine Learning, Large Language Models, Deep Neural Networks, Classification Systems, Clustering, Label Propagation, Natural Language Processing, Computer Vision, Active learning, and Artificial Intelligence. S/he has a strong publication record at top relevant academic venues and experience in launching products/features in the industry. Do you want the excitement of experimenting with cutting edge Large Language Models (LLMs), machine learning, natural language processing, computer vision, and active learning models to solve real world problems at scale? Imagine experimenting with LLMs, with Deep Neural Networks as your daily job and imagine using your model outputs to affect the product discovery of the biggest e-commerce retailer in the world. Imagine doing research inside of an Amazon team that is always looking to deploy creative solutions to real world problems in product discovery. Your research findings are directly related to Amazon’s customer experiences and impact millions of customers, ingesting images, text and all the structured and unstructured attributes in the Amazon catalog to drive true understanding of products at scale. Amazon Science gives you insight into the company’s approach to customer-obsessed scientific innovation. Amazon fundamentally believes that scientific innovation is essential to being the most customer-centric company in the world. It’s the company’s ability to have an impact at scale that allows us to attract some of the brightest minds in artificial intelligence and related fields. Our scientists continue to publish, teach, and engage with the academic community, in addition to utilizing our working backwards method to enrich the way we live and work. Please visit https://www.amazon.science for more information. A day in the life You will work with an Amazon team that builds creative solutions to real world problems. Your team will own devising the strategy and execution plans that power initiatives ranging from: developing tuning artifacts on top of foundational LLMs, training ML models, performing fact extraction, automatic detection of missing product information, active learning mechanisms for scaling human tasks, building applications for distilling product information, building mechanisms to analyze product composition, ingest images, text, and unstructured data to drive deep understanding of products at scale. About the team The team's mission is to infer knowledge, understand, classify, derive product facts for all Amazon products entering the Catalog. The work is critical to power the Amazon product detail pages experiences, Search, Navigation and impacting millions of customers. This is an already formed team with experience leading programs spanning services and ML initiatives supporting all countries and languages. The candidate collaborates closely with Scientists, Software Developers, and has exposure to multiple peer teams at Amazon who rely on this team's developments.

Have you ever wondered how Amazon predicts when your order will arrive and how we ensure that it actually arrives on at the promised date/time? Have you wondered where all those Amazon semi-trucks on the road are headed? Are you passionate about increasing efficiency and reducing carbon footprint? Does the idea of having worldwide impact on Amazon's logistics network including our planes, trucks, and vans sound exciting to you? If so, then we want to talk with you! At Amazon's Supply Chain Optimization Technologies (SCOT), we are tasked with optimizing the fulfilment on customer orders so that we fulfil all orders worldwide in the most intelligent manner while ensuring Amazon customers get their orders on time. Amazon Fulfillment Planning & Execution (FPX) Science team within SCOT- Fulfilment Optimization group is seeking Manager Research Science with expertise in Machine Learning and/or Optimization and a proven record of leading scientists and solving business problems through scalable ML solutions. FPX Science tackles some of the most mathematically complex challenges in transportation planning and execution space to improve Amazon's operational efficiency worldwide. We own Amazon’s global fulfilment center and transportation planning and execution. The team also owns the short-term network planning and execution that determines the optimal flow of customer orders through Amazon fulfilment network. This includes developing sophisticated math models and controllers that assign orders to fulfilment centers to be picked and packed and then planning the optimal ship method in terms of cost, speed and carbon impact to deliver to the customer. These plans drive downstream decisions that are in the billions of dollars at Amazon Scale worldwide. The systems we build are entirely in-house, and are on the cutting edge of both academic and applied research in large scale supply chain planning, optimization, machine learning and statistics. These systems operate at various scales, from real-time decision system that completes thousands of transactions per seconds, to large scale distributed system that optimize Amazon’s fulfilment network. As Amazon continues to build and expand the first party delivery network, this role will be critical to realize this vision. Your team and tech solution will have large impacts to the physical supply chain of Amazon, and play a key role in improving Amazon consumer business’s long-term profitability. If you are interested in diving into a multi-discipline, high impact space this is the team for you. We’re looking for a passionate, results-oriented, and inventive Scientist who can lead from the front towards developing and deploying ML models for our outbound transportation planning systems. In addition, you will be working on design, development and evaluation of highly innovative ML models for solving complex business problems in the area of outbound transportation planning systems. The position is located at Bellevue, WA, just next to Seattle with beautiful outdoors and great city life. Watch http://bit.ly/amazon-scot to get the big picture. Key job responsibilities As a Manager of Research Science within FPX Science team, you will lead a team of research and applied scientists towards designing and deploy solutions that will likely draw from a range of scientific areas such as supervised, semi-supervised and unsupervised learning, reinforcement learning, advanced statistical modeling, and graph models. You will 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, research scientists, statisticians, and software engineers to integrate scientific work into production systems. You will bring deep technical expertise in the area of Machine Learning, and will play an integral part in building Amazon's Fulfillment Optimization systems. Other responsibilities include: * Lead a team of research and applied scientists towards design, development and evaluation of highly innovative ML models for solving complex business problems. * Technically lead and mentor the scientists on the team. * Research and apply the latest ML techniques and best practices from both academia and industry. * Use and analytical techniques to create scalable solutions for business problems. * Work closely with software engineering teams to build model implementations and integrate successful models and algorithms in production systems at very large scale. * Establish scalable, efficient, automated processes for large scale data analyses, model development, model validation and model implementation. A day in the life In this critical role, you will be a technical leader in operations research or machine learning with significant scope, impact, and visibility. Your solutions have the potential to drive billions of dollars in impact for Amazon's supply chain globally. As a science manager on the team, you will engage in all facets of the process from ideation, business analysis and scientific research to development and deployment of advanced models. We are seeking someone who wants to lead projects that require innovative thinking and deep technical problem-solving skills to create production-ready machine learning solutions. A successful candidate is 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. 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. We look for individuals who know how to deliver results and show a desire to develop themselves, their team, and their career. About the team Fulfillment Planning & Execution Science team contains a group of scientists with different technical backgrounds including Machine Learning and Operations Research, who will collaborate closely with you on your projects. Our team directly supports critical functional areas across Fulfillment Optimization and the research needs of the corresponding product and engineering teams. We tackle some of the most mathematically complex challenges in facility and transportation planning and execution to improve Amazon's operational efficiency worldwide and at a scale that is unique to Amazon. We often seek the opportunity of applying hybrid techniques in the space of Operations Research and Machine Learning to tackle some of our biggest technical challenges. We disambiguate complex supply chain problems and create ML and optimization solutions to solve those problems at scale.

Conversational AI ModEling and Learning (CAMEL) team is part of Amazon Artificial General Intelligence (AGI) organization where our mission is to create a best-in-class Conversational AI that is intuitive, intelligent, and responsive, by developing superior Large Language Models (LLM) solutions and services which increase the capabilities built into the model and which enable utilizing thousands of APIs and external knowledge sources to provide the best experience for each request across millions of customers and endpoints. We are looking for a passionate, talented, and resourceful Applied Scientist in the field of LLM, Artificial Intelligence (AI), Natural Language Processing (NLP) and/or Information Retrieval, to invent and build scalable solutions for a state-of-the-art context-aware conversational AI. A successful candidate will have strong machine learning background and a desire to push the envelope in one or more of the above areas. The ideal candidate would also have hands-on experiences in developing LLM solution, enjoy operating in dynamic environments, be self-motivated to take on challenging problems to deliver big customer impact, moving fast to ship solutions and then iterating on user feedback and interactions. Key job responsibilities As an Applied Scientist, you will leverage your technical expertise and experience to collaborate with other talented applied scientists and engineers to research and develop novel algorithms and modeling techniques to reduce friction and enable natural and contextual conversations. You will analyze, understand and improve user experiences by leveraging Amazon’s heterogeneous data sources and large-scale computing resources to accelerate advances in artificial intelligence. You will work on core LLM technologies, including developing best-in-class modeling, prompt optimization algorithms to enable Conversation AI use cases. Your work will directly impact our customers in the form of novel products and services .

The Team: Amazon Go is a new kind of store with no lines and no checkout—you just grab and go! Customers simply use the Amazon Go app to enter the store, take what they want from our selection of fresh, delicious meals and grocery essentials, and go! Our checkout-free shopping experience is made possible by our Just Walk Out Technology, which automatically detects when products are taken from or returned to the shelves and keeps track of them in a virtual cart. When you’re done shopping, you can just leave the store. Shortly after, we’ll charge your Amazon account and send you a receipt. Check it out at amazon.com/go. Designed and custom-built by Amazonians, our Just Walk Out Technology uses a variety of technologies including computer vision, sensor fusion, and advanced machine learning. Innovation is part of our DNA! Our goal is to be Earths’ most customer centric company and we are just getting started. We need people who want to join an ambitious program that continues to push the state of the art in computer vision, machine learning, distributed systems and hardware design. The Role: Everyone on the team needs to be entrepreneurial, wear many hats and work in a highly collaborative environment that’s more startup than big company. We’ll need to tackle problems that span a variety of domains: computer vision, image recognition, machine learning, real-time and distributed systems. As a Machine Learning or Computer Vision Research Scientist, you will help solve a variety of technical challenges and mentor other engineers. You will tackle challenging, novel situations every day and given the size of this initiative, you’ll have the opportunity to work with multiple technical teams at Amazon in different locations. You should be comfortable with a degree of ambiguity that’s higher than most projects and relish the idea of solving problems that, frankly, haven’t been solved at scale before - anywhere. Along the way, we guarantee that you’ll learn a ton, have fun and make a positive impact on millions of people. 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.

The Team: Amazon Go is a new kind of store with no lines and no checkout—you just grab and go! Customers simply use the Amazon Go app to enter the store, take what they want from our selection of fresh, delicious meals and grocery essentials, and go! Our checkout-free shopping experience is made possible by our Just Walk Out Technology, which automatically detects when products are taken from or returned to the shelves and keeps track of them in a virtual cart. When you’re done shopping, you can just leave the store. Shortly after, we’ll charge your Amazon account and send you a receipt. Check it out at amazon.com/go. Designed and custom-built by Amazonians, our Just Walk Out Technology uses a variety of technologies including computer vision, sensor fusion, and advanced machine learning. Innovation is part of our DNA! Our goal is to be Earths’ most customer centric company and we are just getting started. We need people who want to join an ambitious program that continues to push the state of the art in computer vision, machine learning, distributed systems and hardware design. The Role: Everyone on the team needs to be entrepreneurial, wear many hats and work in a highly collaborative environment that’s more startup than big company. We’ll need to tackle problems that span a variety of domains: computer vision, image recognition, machine learning, real-time and distributed systems. As a Machine Learning or Computer Vision Research Scientist, you will help solve a variety of technical challenges and mentor other engineers. You will tackle challenging, novel situations every day and given the size of this initiative, you’ll have the opportunity to work with multiple technical teams at Amazon in different locations. You should be comfortable with a degree of ambiguity that’s higher than most projects and relish the idea of solving problems that, frankly, haven’t been solved at scale before - anywhere. Along the way, we guarantee that you’ll learn a ton, have fun and make a positive impact on millions of people. 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.

Applied Scientist, CMT, Amazon Bangalore Impact As a member of the CMT team, you'll play a key role in the evolution of our Competitive Monitoring systems to solve significantly complex and interesting technical challenges in Large-scale computing, Distributed systems, Web applications, Data mining, Scalability, Security, and Algorithms to name a few. The team's work directly impacts customer experience at a worldwide scale. Innovation Are you seeking an environment where you can drive innovation? Do you want to apply state-of-the-art computer science and advance information retrieval techniques to solve real world problems of competitive data analysis? Does the challenge of building real time, highly scalable solutions for the most complex online business using innovative technology excite you? Opportunity To meet these challenges, the CMT team is looking for passionate, talented and innovative scientists looking to work on cutting edge technology, from Natural Language processing to optimization to image processing and LLMs. In addition to getting the opportunity to participate in research in several domains, you will lead the solution to complex pricing problems in an extremely agile environment. This role will have the opportunity to learn and work on the most cutting edge generative AI solutions. Come be part of this growing, dynamic and challenging space! Key job responsibilities 1. Research the problem domain and come up with various approaches to solve the problem. 2. Be willing to experiment quickly and fail fast. 3. Collaborate with engineers to come up with the right end to end solution to the business problems. 4. Ideate on future roadmap for science in CMT, and CMT in general.