Careers

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 leveraging the latest advances in generative AI, and Amazon’s tremendous computational resources. What do you get? An unparalleled opportunity to deliver transformational experiences that impact customers everyday lives. Are you passionate about working on disruptive ideas? Are you obsessed with finding and building the most innovative and customer-friendly user experiences? Have you built and launched new experiences that impact shoppers all around the world? This is a unique full-stack opportunity that combines the ability to build exciting, new user experiences for Amazon's customers with the opportunity to work with Generative AI and other advanced techniques to provide the best personalized experience for hundreds of millions of Amazon customers. Key job responsibilities As an Applied Scientist in the Amazon Profiles team in Personalization, your work delivers transformational, AI-powered end-to-end experiences to seek to understand each customer uniquely and deeply. You will use the latest ML and generative AI-powered methods to power new personalized experiences. Amazon Profiles represents a highly-visible charter, with exposure and sponsorship at the S-Team level. We leverage our understanding of each customer to personalize the moments that matter along the Shopping journey, while making it easy for customers to tell us when we get it wrong. We leverage generative AI to use this deep customer insight to help our customers more confidently navigate their shopping journey. We partner closely with teams across Amazon to deliver a unified and cohesive experiences. Come join us as we transform Amazon into a deeply personal and relevant store!

Amazon Music is an immersive audio entertainment service that deepens connections between fans, artists, and creators. From personalized music playlists to exclusive podcasts, concert livestreams to artist merch, Amazon Music is innovating at some of the most exciting intersections of music and culture. We offer experiences that serve all listeners with our different tiers of service: Prime members get access to all the music in shuffle mode, and top ad-free podcasts, included with their membership; customers can upgrade to Amazon Music Unlimited for unlimited, on-demand access to 100 million songs, including millions in HD, Ultra HD, and spatial audio; and anyone can listen for free by downloading the Amazon Music app or via Alexa-enabled devices. Join us for the opportunity to influence how Amazon Music engages fans, artists, and creators on a global scale. Learn more at https://www.amazon.com/music. Amazon Music Search Relevance team is seeking an experienced Applied Scientist who will join a team of experts in the field of machine learning, and work together to break new ground in the world of understanding and classifying different forms of music, and creating interactive experiences to help users find the music they are in the mood for. We work on machine learning problems for music classification, recommender systems, dialogue systems, NLP, and music information retrieval. You'll work in a collaborative environment where you can pursue applied research, with many peta-bytes of data, work on problems that haven’t been solved before, quickly implement and deploy your algorithmic ideas at scale, understand whether they succeed via statistically relevant experiments across millions of customers, and publish your research. You'll see the work you do directly improve the experience of Amazon Music customers on Alexa/Echo, mobile, and web. Key job responsibilities - Use machine learning, deep learning, LLMs and NLP techniques to create scalable solutions for business problems - Analyze and extract relevant information from large amounts of Amazon's data to help automate and optimize key processes - Design, development and evaluation of highly innovative models for predictive learning - Work closely with software engineering teams to drive model implementations and new feature creations - Establish scalable, efficient, automated processes for large scale data analyses, model development, model validation and model implementation - Research and implement novel machine learning and statistical approaches About the team Everyone on our team has a meaningful impact on product features, new directions in music streaming, and customer engagement. We are looking fornew team members across a variety of job functions including software engineering/development, marketing, design, ops and more. Come join us aswe make history by launching exciting new projects in the coming year.Our team is focused on building a personalized, curated, and seamless musicexperience. We want to help our customers discover up-and-coming artists, while also having access to their favorite established musicians. We build systems that are distributed on a large scale, spanning our music apps, web player, and voice-forward audio engagement on mobile and Amazon Echo devices, powered by Alexa to support our customer base. Amazon Music offerings are available in countries around the world, and our applications support our mission of delivering music to customers in new and exciting ways that enhance their day-to-day lives.

The Amazon Search team creates powerful, customer-focused search solutions and technologies. Whenever a customer visits an Amazon site worldwide and types in a query or browses through product categories, Amazon Product Search services go to work. We design, develop, and deploy high performance, fault-tolerant distributed search systems used by millions of Amazon customers every day. Our Search Relevance team works to maximize the quality and effectiveness of the search experience for visitors to Amazon websites worldwide. The Search Relevance team focuses on several technical areas for improving search quality. In this role, you will invent universally applicable signals and algorithms for training machine-learned ranking models. The relevance improvements you make will help millions of customers discover the products they want from a catalog containing millions of products. You will work on problems such as predicting the popularity of new products, developing new ranking features and algorithms that capture unique characteristics, and analyzing the differences in behavior of different categories of customers. The work will span the whole development pipeline, including data analysis, prototyping, A/B testing, and creating production-level components. 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 in our offices located in Palo Alto, California. Please visit https://www.amazon.science for more information

The Rufus team is building foundational LLMs for Amazon Stores that fuse general world knowledge with Amazon e-commerce domain knowledge, to provide new and improved shopping experiences for our customers. We are searching for pioneers who are passionate about technology, innovation, and customer experience, and are ready to make a lasting impact on the industry. You’ll be working with talented scientists, engineers, and technical program managers (TPM) to innovate on behalf of our customers. If you’re fired up about being part of a dynamic, driven team, then this is your moment to join us on this exciting journey!

The Alexa Customer Journeys team is looking for a passionate, highly skilled and inventive Senior Applied Scientist with strong machine learning background to lead the development and implementation of state-of-the-art ML systems for personalizing large-scale, high-quality conversational assistant systems. As a Senior 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 engineers, product managers, and scientists 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 about the arc of development of 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 - Mentor and guide junior scientists and engineers, and contribute to the overall growth and development of the team

As a Sr. Data Scientist on the Targeting & Tooling team, you will have the opportunity to gain deep insights into customer needs and accelerate our go-to-market strategies. Leveraging cutting-edge AI and machine learning techniques, you will provide actionable and understandable recommendations that enable our sales teams to anticipate customer requirements and identify those best positioned to benefit from Amazon Web Services (AWS) cloud solutions. You will work closely with stakeholders throughout the organization to consume, analyze, and interpret customer data from a variety of sources. You will convey technical concepts clearly to both technical and non-technical audiences. You will identify trends and tell compelling data stories. You will help improve customer experiences and drive business results as a key member of the World Wide Specialist Organization (WWSO) team. Our team is dedicated to supporting new members. We have a broad mix of experience levels and tenures, and we’re building an environment that celebrates knowledge sharing and mentorship. We care about your career growth and strive to assign projects based on what will help each team member develop into a better-rounded professional and enable them to take on more complex tasks in the future. Here at AWS, we embrace our differences. We are committed to furthering our culture of inclusion. We have ten employee-led affinity groups, reaching 40,000 employees in over 190 chapters globally. We have innovative benefit offerings, and we host annual and ongoing learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences. Amazon’s culture of inclusion is reinforced within our 16 Leadership Principles, which remind team members to seek diverse perspectives, learn and be curious, and earn trust. Our team also puts a high value on work-life balance. Striking a healthy balance between your personal and professional life is crucial to your happiness and success here, which is why we aren’t focused on how many hours you spend at work or online. Instead, we’re happy to offer a flexible schedule so you can have a more productive and well-balanced life—both in and outside of work. Key job responsibilities - Leverage machine learning and advanced analytical techniques to extract meaningful insights from large, complex data sets related to GenAI, Enterprise Applications, Containerized Applications, and Serverless applications. - Build, evaluate, and optimize data science models to solve focused business problems such as improving customer targeting, predicting product demand, and identifying growth opportunities. - Work closely with Go-To-Market, field teams, and product teams to understand key challenges and inform strategic initiatives with data-driven recommendations. - Communicate analysis, results and recommendations clearly to key stakeholders to influence Go-To-Market strategy. - Keep updated on latest data science and machine learning advancements and evaluate new methods for applicability to current business problems. - Develop best practices for building, evaluating, deploying and monitoring analytical models in production environments. A day in the life As a Data Scientist on the Targeting and Tooling team, a typical day may start by meeting with our go-to-market teams to deeply understand the customer challenges they want to solve, the AWS services and technologies that can address those needs, and the key success metrics for their initiatives. You will translate business goals into focused, data-driven projects. This involves identifying leading indicators and unique data sources to model ideal customer profiles and high-potential targets. About the team The Targeting and Tooling team plays a crucial role in enabling AWS go-to-market teams to achieve their strategic initiatives. We leverage cutting-edge data science and machine learning techniques to equip our sales and marketing teams with actionable insights that accelerate cloud transformation. Our core mission is to provide data-driven targeting that allows AWS go-to-market teams to anticipate customer needs early and identify high-potential opportunities. Working closely with stakeholders, we first strive to thoroughly understand existing solutions and offerings along with their target outcomes. With this context, we develop innovative predictive models that identify both current ideal customers and those likely to expand their AWS footprint over time. In addition, we create novel metrics and adoption models that measure the overall success of the initiative. The Targeting and Tooling group produces the actionable intelligence that directly informs go-to-market strategies worldwide. The insights we uncover help prioritize accounts and opportunities to drive AWS growth. As a team of elite data scientists and machine learning engineers, we shape plans that support sales, marketing, and cloud adoption success across all industries.

Amazon is investing heavily in building a world class advertising business and we are responsible for 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. We are highly motivated, collaborative and fun-loving with an entrepreneurial spirit and bias for action. With a broad mandate to experiment and innovate, we are growing at an unprecedented rate with a seemingly endless range of new opportunities. The ATT team, based in Bangalore, is responsible for ensuring that ads are relevant and is of good quality, leading to higher conversion for the sellers and providing a great experience for the customers. We deal with one of the world’s largest product catalog, handle billions of requests a day with plans to grow it by order of magnitude and use automated systems to validate tens of millions of offers submitted by thousands of merchants in multiple countries and languages. In this role, you will build and develop ML models to address content understanding problems in Ads. These models will rely on a variety of visual and textual features requiring expertise in both domains. These models need to scale to multiple languages and countries. You will collaborate with engineers and other scientists to build, train and deploy these models. As part of these activities, you will develop production level code that enables moderation of millions of ads submitted each day.

The Alexa Conversational Assistants Services (CAS) org is looking for a Principal Applied Scientist with a background in Natural Language Processing, Machine/Deep Learning, and Large Language Models (LLMs). You will be working with a team of applied and research scientists to enhance existing features and explore new possibilities with LLM empowerment. You will own high visibility programs with broad visibility and impact. You will interact with a cross-functional team of science, product, and engineering leaders. As a Principal Scientist within Alexa, you are a trusted part of the technical leadership. You bring business and industry context to science and technology decisions. You set the standard for scientific excellence and make decisions that affect the way we build and integrate algorithms. You solicit differing views across the organization and are willing to change your mind as you learn more. Your artifacts are exemplary and often used as reference across organization. You are a hands-on scientific leader. Your solutions are exemplary in terms of algorithm design, clarity, model structure, efficiency, and extensibility. You tackle intrinsically hard problems, acquiring expertise as needed. You decompose complex problems into straightforward solutions. You amplify your impact by leading scientific reviews within your organization or at your location. You scrutinize and review experimental design, modeling, verification and other research procedures. You probe assumptions, illuminate pitfalls, and foster shared understanding. You align teams toward coherent strategies. You educate, keeping the scientific community up to date on advanced techniques, state of the art approaches, the latest technologies, and trends. You help managers guide the career growth of other scientists by mentoring and play a significant role in hiring and developing scientists and leads. We’re looking for a passionate, talented, and inventive Principal Scientist to help build industry-leading conversational technologies that customers love. Our mission is to push the envelope in Artificial Intelligence (AI), Natural Language Understanding (NLU), Machine Learning (ML), Dialog Management, Automatic Speech Recognition (ASR), and Audio Signal Processing, in order to provide the best-possible experience for our customers. As a Principal Artificial Intelligence Scientist, you will work with talented peers to develop novel algorithms and modeling techniques to advance the state of the art in spoken language understanding and dialog systems. You will leverage Amazon’s heterogeneous data sources and large-scale computing resources to accelerate advances in artificial intelligence. You will mentor Senior scientists, and work in a fast paced team environment. Your work will directly impact our customers in the form of novel products and services that make use of speech and language technology. Key job responsibilities You will be responsible for defining key research directions, adopting or inventing new machine learning techniques, conducting rigorous experiments, publishing results, and ensuring that research is translated into practice. You will develop long-term strategies, persuade teams to adopt those strategies, propose goals and deliver on them. You will also participate in organizational planning, hiring, mentorship and leadership development. You will be technically fearless and with a passion for building scalable science and engineering solutions. You will serve as a key scientific resource in full-cycle development (conception, design, implementation, testing to documentation, delivery, and maintenance). About the team Alexa is the groundbreaking cloud-based intelligent agent that powers Echo and other devices designed around your voice. Our team is creating the science and technology behind Alexa. We’re working hard, having fun, and making history. Come join our team! You will have an enormous opportunity to impact the customer experience, design, architecture, and implementation of a cutting edge product used every day by people you know.

Amazon Search is looking for an Applied Scientist to build the next-generation Autocomplete and Spelling Correction experience. Autocomplete provides real-time suggestions as customers type in the search box. It serves as a virtual assistant on customer’s shopping journey. Our suggestions complete customers’ thoughts and help them to explore Amazon’s vast product offering. Spelling correction recovers the spelling errors in the queries, allowing customers to search effortlessly in any language they prefer, without worrying about making spelling mistakes. You will have the opportunities to leverage the latest developments in Natural Language Processing, Deep Learning, and Reinforcement Learning to re-invent customers’ shopping experience. Your work will touch the life of hundreds of millions customers and deliver billion-dollar business impact. You will love the job if you enjoy brining the cutting-edge research to people’s (and yours) day-to-day life. It’s a great feeling to realize the model you deployed yesterday has helped your shopping journey today. You will work closely with scientists and engineers to do fast-pace model development and experiment iterations. You will have access to Amazon’s rich datasets, AWS’s massive computation power, and science and engineering leaders across the company. As an applied scientist, you will Drive the science vision and roadmap. Develop data-driven solutions for the real-world, large scale problems. Deliver and maintain software and models in the production environment. Lead cross-functional collaborations between product, design, and engineering.

Are you excited about using decision (optimization) and data (ML) sciences to make multi-million dollar decisions more Data, Science and Analytics Driven? Are you interested in price optimization, promotion planning and what-if simulations to enable in-period promotion and long-term financial planning? Do you want to be a part of a multi disciplinary science team focuses on tackling some of the big business problems with within the Devices business at Amazon? Then this could be the role for you! The Amazon Devices & Services Demand Planning and Product Development (DEPD) team is seeking an outstanding scientist with strong analytical and communication skills to help with pricing optimization and promotion planning for the entire Amazon device family of products and services. Amazon Devices represents a highly complex space with 100+ products across several product categories that includes Echo, Kindle, Fire Tablets, Amazon TVs, Amazon Fire TV sticks, Ring, and other smart home devices for sale both online and in offline retailers globally. We develop scalable and robust state-of-the-art deterministic and stochastic optimization models and algorithms, and what-if scenario planning simulation tools with (linear and dynamic) price optimization and promotion planning. With better price optimization and promotion planning, we manage demand and drive down promotion and supply chain costs, enabling the offer of lower prices and better in-stock selection for our customers globally. We are looking for an Applied Scientist with background in Operations Research, Optimization, Supply Chain, Industrial & Systems Engineering and/or Simulation. In this role, you will have an opportunity to both develop advanced scientific solutions, and drive critical customer and business impacts. You will play a key role to drive end-to-end solutions from understanding our business requirements, exploring a large amount of historical data, building, managing and improving optimization, simulation and HOTW decision models, building prototypes and products, and exploring conceptually new solutions, to working with partner teams for prod deployment that will be used primarily for Promotion Optimization and Scenario Planning Capabilities for in-period promotion, and long-term financial planning. You will collaborate closely with scientists, engineering peers as well as business stakeholders. You will be at the heart of a growing and exciting focus area for Amazon Devices and Services. You are an individual with outstanding analytical abilities, excellent communication skills, and are comfortable working with cross-functional teams and systems. You will be responsible for researching, prototyping, experimenting, analyzing prescriptive optimization models and developing smart automation solutions. Key job responsibilities - Research, design, prototype, experiment and implement advanced optimization algorithms and models to address challenging business problems by using modeling languages such as Python; participate in the production level deployment - Collaborate with cross-functional teams including product management, marketing, and operations to translate model insights into actionable business strategies - Develop and maintain optimization frameworks, libraries, and tools to enable scalable and efficient optimization and automation capabilities - Analyze optimization results, identify bottlenecks, and continuously improve the performance and accuracy of optimization models - Stay up-to-date on the latest academic research and industry best practices in optimization techniques and tools, and identify opportunities to apply new approaches - Create and track accuracy and performance metrics (both technical and business metrics) - Create, enhance, and maintain technical documentation, and present to other scientists, engineers and business leaders - Drive best practices on the team; mentor and guide junior members to achieve their career growth potential A day in the life Our team is dedicated to supporting new members. We have a broad mix of experience levels and tenures, and we’re building an environment that celebrates knowledge sharing and mentorship. We care about your career growth and strive to assign projects based on what will help each team member develop into a better-rounded professional and enable them to take on more complex tasks in the future. About the team The vision for Cognitive Science Team is to deliver science-enabled HOTW demand planning and shaping solutions for Devices Product Lines to support our partners’ decision making processes. We will accomplish our vision by (1) utilizing accelerated applied science with optimization, simulation, scenario planning, Machine Learning and Generative AI (in 2025), (2) performing rapid research & innovation, developing incremental products, and automating processes, (3) developing optimized price and promotion planning, (4) developing high confidence long-lead time marquee unit demand forecasts for Amazon Devices.