Careers

Are you passionate about automation, optimization, knowledge extraction, and artificial intelligence through the use of Machine Learning, Computer Vision, Optimization, Natural Language Processing, and Recommender systems? We have a team of experienced scientists with a critical business mission making revolutionary leaps forward in these spaces. On this team you will work with an immense and diverse corpus of text, image, audio, and machine telemetry data to build generative and discriminative models for optimizing large-scale manufacturing and fulfillment processes, analyze and model customer reading behavior to measure engagement and detect risks, and build AI-based systems for helping indie authors make their businesses successful. This will involve combining methods from several science domains with domain knowledge across multiple businesses into sophisticated ML workflows. Our team has mature areas and green-field opportunities. We offer scientific autonomy, value end-to-end ownership, and have a strong customer-focused culture. As an Applied Scientist at Amazon, you will connect with world leaders in your field working on similar problems. You will be working with large distributed systems of data and providing technical leadership to the product managers, teams, and organizations building machine learning solutions. You will be tackling Machine Learning challenges in Supervised, Unsupervised, and Semi-supervised Learning; utilizing modern methods such as deep learning and classical methods from statistical learning theory, detection, estimation. Senior Applied Scientists are specialists with the deep expertise to drive the scientific vision for our products. They are externally aware of the state-of-the-art in their respective field of expertise and are constantly focused on advancing that state-of-the-art for improving Amazon’s products and services. Come join us as we revolutionize the book industry and deliver an amazing experience to our Kindle authors and readers. Kindle Direct Publishing (KDP) and Print On Demand (POD) have empowered a new wave of self-motivated creators, tearing down barriers that once blocked writers from reaching readers. Our team builds rich applications and systems that empower anyone to realize their dream of becoming a published author. We strive to provide an experience that is powerful, yet simple to use and accessible to all. We focus on building tools that enable authors to design high quality digital and print books, reaching readers all around the world. This role will help ensure we maintain the trust of both our Authors and Readers by ensuring all books published to Amazon meet our standards. Great candidates for this position will be experts in the areas of data science, machine learning, computer vision, optimization, NLP, or statistics. You will have hands-on experience with multiple science initiatives as well as be able to balance technical leadership with strong business judgment to make the right decisions about technology, models and methodological choices. You will strive for simplicity, and demonstrate significant creativity and high judgment. Come join us as we continue to revolutionize the book industry!

The Ads Measurement Science team in the Measurement, Ad Tech, and Data Science (MADS) team of Amazon Ads serves a centralized role developing solutions for a multitude of performance measurement products. We create solutions which measure the comprehensive impact of their ad spend, including sales impacts both online and offline and across timescales, and provide actionable insights that enable our advertisers to optimize their media portfolios. We leverage a host of scientific technologies to accomplish this mission, including Generative AI, classical ML, Causal Inference, Natural Language Processing, and Computer Vision. We are hiring an Economist on the team to develop the next generation of incrementality measurement products, capturing the effect of advertising in driving sales as well as the effects of measurement tools on advertiser engagement with Amazon. As an Economist on the team, you will lead the design, implementation, and validation of large-scale causal inference methodologies to capture these properties. You will communicate your results with science and business leaders, and partner with other scientists and engineers to carry solutions into production. Key job responsibilities Leverage deep expertise in causal inference to develop robust, causally grounded ads measurement solutions Disambiguate problems to propose clear evaluation frameworks and success criteria Work autonomously and write high quality technical documents Partner closely with other scientists to deliver large, multi-faceted technical projects Share and publish works with the broader scientific community through meetings and conferences Communicate clearly to both technical and non-technical audiences and leaders Contribute new ideas that shape the direction of the team's work Mentor more junior scientists and participate in the hiring process

Are you passionate about automation, optimization, knowledge extraction, and artificial intelligence through the use of Machine Learning, Computer Vision, Optimization, Natural Language Processing, and Recommender systems? We have a team of experienced scientists with a critical business mission making revolutionary leaps forward in these spaces. On this team you will work with an immense and diverse corpus of text, image, audio, and machine telemetry data to build generative and discriminative models for optimizing large-scale manufacturing and fulfillment processes, analyze and model customer reading behavior to measure engagement and detect risks, and build AI-based systems for helping indie authors make their businesses successful. This will involve combining methods from several science domains with domain knowledge across multiple businesses into sophisticated ML workflows. Our team has mature areas and green-field opportunities. We offer scientific autonomy, value end-to-end ownership, and have a strong customer-focused culture. As an Applied Scientist at Amazon, you will connect with world leaders in your field working on similar problems. You will be working with large distributed systems of data and providing technical leadership to the product managers, teams, and organizations building machine learning solutions. You will be tackling Machine Learning challenges in Supervised, Unsupervised, and Semi-supervised Learning; utilizing modern methods such as deep learning and classical methods from statistical learning theory, detection, estimation. Applied Scientists are specialists with the deep expertise to drive the scientific vision for our products. They are externally aware of the state-of-the-art in their respective field of expertise and are constantly focused on advancing that state-of-the-art for improving Amazon’s products and services. Come join us as we revolutionize the book industry and deliver an amazing experience to our Kindle authors and readers. Key job responsibilities Great candidates for this position will be experts in the areas of data science, machine learning, computer vision, optimization, NLP, or statistics. You will have hands-on experience with multiple science initiatives as well as be able to balance technical leadership with strong business judgment to make the right decisions about technology, models and methodological choices. You will strive for simplicity, and demonstrate significant creativity and high judgment. About the team Kindle Direct Publishing (KDP) and Print On Demand (POD) have empowered a new wave of self-motivated creators, tearing down barriers that once blocked writers from reaching readers. Our team builds rich applications and systems that empower anyone to realize their dream of becoming a published author. We strive to provide an experience that is powerful, yet simple to use and accessible to all. We focus on building systems that enable authors to design high quality digital and print books, reaching readers all around the world. This role will help ensure we maintain the trust of both our Authors and Readers by ensuring all books published to Amazon meet our standards.

Are you passionate about automation, optimization, knowledge extraction, and artificial intelligence through the use of Machine Learning, Computer Vision, Optimization, Natural Language Processing, and Recommender systems? We have a team of experienced scientists with a critical business mission making revolutionary leaps forward in these spaces. On this team you will work with an immense and diverse corpus of text, image, audio, and machine telemetry data to build generative and discriminative models for optimizing large-scale manufacturing and fulfillment processes, analyze and model customer reading behavior to measure engagement and detect risks, and build AI-based systems for helping indie authors make their businesses successful. This will involve combining methods from several science domains with domain knowledge across multiple businesses into sophisticated ML workflows. Our team has mature areas and green-field opportunities. We offer scientific autonomy, value end-to-end ownership, and have a strong customer-focused culture. As a Senior Applied Scientist at Amazon, you will connect with world leaders in your field working on similar problems. You will be working with large distributed systems of data and providing technical leadership to the product managers, teams, and organizations building machine learning solutions. You will be tackling Machine Learning challenges in Supervised, Unsupervised, and Semi-supervised Learning; utilizing modern methods such as deep learning and classical methods from statistical learning theory, detection, estimation. Senior Applied Scientists are specialists with the deep expertise to drive the scientific vision for our products. They are externally aware of the state-of-the-art in their respective field of expertise and are constantly focused on advancing that state-of-the-art for improving Amazon’s products and services. Come join us as we revolutionize the book industry and deliver an amazing experience to our Kindle authors and readers. Key job responsibilities Great candidates for this position will be experts in the areas of data science, machine learning, computer vision, optimization, NLP, or statistics. You will have hands-on experience with multiple science initiatives as well as be able to balance technical leadership with strong business judgment to make the right decisions about technology, models and methodological choices. You will strive for simplicity, and demonstrate significant creativity and high judgment. About the team Kindle Direct Publishing (KDP) and Print On Demand (POD) have empowered a new wave of self-motivated creators, tearing down barriers that once blocked writers from reaching readers. Our team builds rich applications and systems that empower anyone to realize their dream of becoming a published author. We strive to provide an experience that is powerful, yet simple to use and accessible to all. We focus on building systems that enable authors to design high quality digital and print books, reaching readers all around the world. This role will help ensure we maintain the trust of both our Authors and Readers by ensuring all books published to Amazon meet our standards.

Are you passionate about automation, optimization, knowledge extraction, and artificial intelligence through the use of Machine Learning, Computer Vision, Optimization, Natural Language Processing, and Recommender systems? We have a team of experienced scientists with a critical business mission making revolutionary leaps forward in these spaces. On this team you will work with an immense and diverse corpus of text, image, audio, and machine telemetry data to build generative and discriminative models for optimizing large-scale manufacturing and fulfillment processes, analyze and model customer reading behavior to measure engagement and detect risks, and build AI-based systems for helping indie authors make their businesses successful. This will involve combining methods from several science domains with domain knowledge across multiple businesses into sophisticated ML workflows. Our team has mature areas and green-field opportunities. We offer scientific autonomy, value end-to-end ownership, and have a strong customer-focused culture. As an Applied Scientist at Amazon, you will connect with world leaders in your field working on similar problems. You will be working with large distributed systems of data and providing technical leadership to the product managers, teams, and organizations building machine learning solutions. You will be tackling Machine Learning challenges in Supervised, Unsupervised, and Semi-supervised Learning; utilizing modern methods such as deep learning and classical methods from statistical learning theory, detection, estimation. Senior Applied Scientists are specialists with the deep expertise to drive the scientific vision for our products. They are externally aware of the state-of-the-art in their respective field of expertise and are constantly focused on advancing that state-of-the-art for improving Amazon’s products and services. Come join us as we revolutionize the book industry and deliver an amazing experience to our Kindle authors and readers. Key job responsibilities Great candidates for this position will be experts in the areas of data science, machine learning, computer vision, optimization, NLP, or statistics. You will have hands-on experience with multiple science initiatives as well as be able to balance technical leadership with strong business judgment to make the right decisions about technology, models and methodological choices. You will strive for simplicity, and demonstrate significant creativity and high judgment. About the team Kindle Direct Publishing (KDP) and Print On Demand (POD) have empowered a new wave of self-motivated creators, tearing down barriers that once blocked writers from reaching readers. Our team builds rich applications and systems that empower anyone to realize their dream of becoming a published author. We strive to provide an experience that is powerful, yet simple to use and accessible to all. We focus on building systems that enable authors to design high quality digital and print books, reaching readers all around the world. This role will help ensure we maintain the trust of both our Authors and Readers by ensuring all books published to Amazon meet our standards.

Are you passionate about automation, optimization, knowledge extraction, and artificial intelligence through the use of Machine Learning, Computer Vision, Optimization, Natural Language Processing, and Recommender systems? We have a team of experienced scientists with a critical business mission making revolutionary leaps forward in these spaces. On this team you will work with an immense and diverse corpus of text, image, audio, and machine telemetry data to build generative and discriminative models for optimizing large-scale manufacturing and fulfillment processes, analyze and model customer reading behavior to measure engagement and detect risks, and build AI-based systems for helping indie authors make their businesses successful. This will involve combining methods from several science domains with domain knowledge across multiple businesses into sophisticated ML workflows. Our team has mature areas and green-field opportunities. We offer scientific autonomy, value end-to-end ownership, and have a strong customer-focused culture. As an Applied Scientist at Amazon, you will connect with world leaders in your field working on similar problems. You will be working with large distributed systems of data and providing technical leadership to the product managers, teams, and organizations building machine learning solutions. You will be tackling Machine Learning challenges in Supervised, Unsupervised, and Semi-supervised Learning; utilizing modern methods such as deep learning and classical methods from statistical learning theory, detection, estimation. Senior Applied Scientists are specialists with the deep expertise to drive the scientific vision for our products. They are externally aware of the state-of-the-art in their respective field of expertise and are constantly focused on advancing that state-of-the-art for improving Amazon’s products and services. Come join us as we revolutionize the book industry and deliver an amazing experience to our Kindle authors and readers. Key job responsibilities Great candidates for this position will be experts in the areas of data science, machine learning, computer vision, optimization, NLP, or statistics. You will have hands-on experience with multiple science initiatives as well as be able to balance technical leadership with strong business judgment to make the right decisions about technology, models and methodological choices. You will strive for simplicity, and demonstrate significant creativity and high judgment. About the team Kindle Direct Publishing (KDP) and Print On Demand (POD) have empowered a new wave of self-motivated creators, tearing down barriers that once blocked writers from reaching readers. Our team builds rich applications and systems that empower anyone to realize their dream of becoming a published author. We strive to provide an experience that is powerful, yet simple to use and accessible to all. We focus on building systems that enable authors to design high quality digital and print books, reaching readers all around the world. This role will help ensure we maintain the trust of both our Authors and Readers by ensuring all books published to Amazon meet our standards.

Amazon Supply Chain forms the backbone of the fastest growing e-commerce business in the world. The sheer growth of the business and the company's mission "to be Earth’s most customer-centric company” makes the customer fulfillment business bigger and more complex with each passing year. The EU SC Science Optimization team is looking for an exceptionally talented Scientist to tackle complex and ambiguous optimization and forecasting problems for our EU/NA fulfillment network. The team owns the optimization of our Supply Chain from our suppliers to our customers. We are also responsible for analyzing the performance of our Supply Chain end-to-end and deploying Operations Research, Machine Learning, Statistics and Econometrics models to improve decision making within our organization, including forecasting, planning and executing our network. We work closely with Supply Chain Optimization Technology (SCOT) teams, who own the systems and the inputs we rely on to plan our networks, the worldwide scientific community, and with our internal EU stakeholders within Supply Chain, Transportation, Store and Finance. We are looking for an experienced candidate having a well-rounded-technical/science background, with a particular expertise in stochastic optimization and probabilistic forecasting, as well as a history of delivering complex scientific projects end-to-end, and is comfortable in developing long term scientific solutions while ensuring the continuous delivery of incremental model improvements and results in an ever-changing operational environment. As an Applied Scientist, you will design, develop and deploy robust and scalable scientific solutions via Operations Research and Machine Learning algorithms, especially in the context of stochastic customer demand and other sources of uncertainty requiring to move past deterministic optimization. You will partner with other tech and science teams, operations, finance to identify opportunities to improve our processes in order to drive efficiency improvements in our Fulfillment Center network flows. This role requires a self-starter aptitude for independent initiative and the ability to influence partner scientific and operational teams so to drive innovation in supply chain planning and execution. You are passionate, results-oriented, and inventive scientist who obsesses over the quality of your solutions and their fast and scalable implementation to address and anticipate customer needs. Key job responsibilities Build state-of-the art, robust and scalable Stochastic Optimization and Probabilistic Forecasting algorithms to drive optimal planning under uncertainty and execution in Amazon end-to-end supply chain Design and engineer algorithms using Cloud-based state-of-the art software development techniques Think multiple steps ahead and develop for long term solutions while continuously delivering incremental improvements to existing ones Prototype fast, ensure early adoption via pilots, integrate feedback into the models, and iterate Operationalize (i.e. deliver) your science solutions by closely partnering with internal customers, understand their needs/blockers and influence their roadmap Lead complex analysis and clearly communicate results and recommendations to leadership Act as an active member of the science community by researching, applying and publishing internally/externally the latest OR/ML techniques from both academia and industry

Take Earth's most customer-centric company. Mix in hundreds of millions of shoppers spending tens of billions of dollars annually, an exciting opportunity to build next-generation shopping experiences, Amazon’s tremendous computational resources, and our extensive e-Commerce experience. What do you get? The most exciting position in the industry. About our organization: Our team is part of Amazon’s Personalization organization, a high-performing group that leverages Amazon’s expertise in machine learning, big data, distributed systems, and user experience design to deliver the best shopping experiences for our customers. We run global experiments and our work has revolutionized e-commerce with features such as "Keep shopping for", "Tap to explore", “Customers who bought this item also bought”, and “Frequently bought together” among others. Amazon’s internal surveys regularly recognize us as one of the best engineering organizations to work for in the company, with visible high-impact work, low operational load, respectful work-life balance, and continual opportunity to learn and grow. You will play a critical role in ideation for the team. We are building the next generation ML systems that powers the biggest shopping engine on earth, and we hope you will join us! Key job responsibilities As an Applied Scientist on the team you will be working on cutting edge ways to help customers find the right products and content on their shopping journey. Our goal is to help customers achieve their objective seamlessly while shopping on Amazon. We are investing in multiple fronts including but not limited to GenerativeAI, LLMs, transformers, sequence models, reinforcement learning, MABs. This is an opportunity to come in on Day0 and influence the science roadmap of one of the most interesting problem spaces at Amazon - understanding the Amazon customer to build deeply personalized and adaptive shopping experiences. We will be working on applying cutting edge science and research into production to elevate the customer experience. You will be part of a multidisciplinary team, working on one of the largest scale machine learning systems in the company. You will hone your skills in areas such as deep learning and reinforcement learning while building scalable industrial systems. As a member of a highly leveraged team of talented engineers and ML scientists, you will have a unique opportunity to help build infrastructure that accesses petabytes of data to produce and deliver models that deliver state of the art customer experiences. About the team Our mission is to delight every Amazon customer with a consistent and adaptive personalized shopping experience. We achieve our mission through investments in large scale machine learning, distributed systems and user experience with the purpose of delivering the future of shopping on Amazon. We are seeking an Applied Scientist to work on step function science improvements to help achieve SOTA results and to help build new Personalization experiences for Amazon customers.

AWS Analytics is looking for a passionate, inventive Applied Scientist with a strong background in either machine learning, programming languages or databases to help create industry-leading analytics experiences powered by generative AI, machine learning, and program analysis. AWS provides a comprehensive set of analytics services for all data analytics needs and enables organizations of all sizes and industries to reinvent their business with data. From storage and management, data governance, actions, and experiences, AWS offers purpose-built services that provide the best price-performance, scalability, and lowest cost. We are a team dedicated to delivering transformative, science-driven analytics experiences for Amazon customers and having fun doing so. Our leadership team fosters an inclusive team culture and encourages work-life balance to bring out the best in each team member. Collaboration and mentorship are key tenets of our fabric. We are a growing team dedicated to supporting new members achieve their aspirations. Key job responsibilities As part of the AWS Analytics science team you will have the opportunity to apply your skills in machine learning, program analysis, and databases to impact some of the largest analytics services in the industry and their customers. You will innovate by designing and building agent-based solutions orchestrating foundation models, machine learning models, and program analyses to simplify AWS customers’ analytics journey and optimize their cost-performance profile. You will collaborate with a talented team of applied science peers to drive scientific impact and with engineering, product, and business leaders to launch your work in production at Amazon scale. A day in the life A mix of the following activities: talking to product leaders and customers to define science features; researching the state of the art and creating science plans to build them; building and rigorously benchmarking the science implementations of such features; partnering with engineering teams to onboard science work and launch it in production; preparing, publishing, and presenting scientific work at top-tier science venues and evangelizing it within the company; upgrading your science knowledge by participating in reading groups and science presentations by internal or external scientists; mentoring applied science interns and science peers in all of the above functions. About the team 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.

AWS Analytics is looking for a passionate, inventive Applied Scientist with a strong background in either machine learning, programming languages or databases to help create industry-leading analytics experiences powered by generative AI, machine learning, and program analysis. AWS provides a comprehensive set of analytics services for all data analytics needs and enables organizations of all sizes and industries to reinvent their business with data. From storage and management, data governance, actions, and experiences, AWS offers purpose-built services that provide the best price-performance, scalability, and lowest cost. We are a team dedicated to delivering transformative, science-driven analytics experiences for Amazon customers and having fun doing so. Our leadership team fosters an inclusive team culture and encourages work-life balance to bring out the best in each team member. Collaboration and mentorship are key tenets of our fabric. We are a growing team dedicated to supporting new members achieve their aspirations. Key job responsibilities As part of the AWS Analytics science team you will have the opportunity to apply your skills in machine learning, program analysis, and databases to impact some of the largest analytics services in the industry and their customers. You will innovate by designing and building agent-based solutions orchestrating foundation models, machine learning models, and program analyses to simplify AWS customers’ analytics journey and optimize their cost-performance profile. You will collaborate with a talented team of applied science peers to drive scientific impact and with engineering, product, and business leaders to launch your work in production at Amazon scale. A day in the life A mix of the following activities: talking to product leaders and customers to define science features; researching the state of the art and creating science plans to build them; building and rigorously benchmarking the science implementations of such features; partnering with engineering teams to onboard science work and launch it in production; preparing, publishing, and presenting scientific work at top-tier science venues and evangelizing it within the company; upgrading your science knowledge by participating in reading groups and science presentations by internal or external scientists; mentoring applied science interns and science peers in all of the above functions. About the team 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.