Careers

Our team drives innovation for the onsite retail shopping site publisher. We collaborate and influence the advertising science community at Amazon across the entire Ads stack— sourcing and ranking ads, bidding into and pricing in the ads auction, experimentation design to measure causal impact of showing ads on shoppers and Amazon vendors, creative development with GenAI, and more. If you’re interested in joining a unique, highly respected advertising group with a relentless focus on the customer, you’ve come to the right place. As we continue building to out our team, we are looking for a Principal Applied Scientist, to lead research, design, experiment and implementation of cutting edge algorithms for complex Stores Display publisher use cases. You will collaborate with Amazon demand programs and front-end teams to influence how the entire advertising stack works end-to-end. You will work with business and finance teams to design experiments that inform tradeoffs across advertiser and shopper goals. You will work collaboratively with software engineers, data engineers, and other scientists on the team to deploy production algorithms that support the billions of ad auctions run daily and set a high bar for science and engineering excellence. This is a rare opportunity to be a foundational member with huge potential for impact and innovating new user experiences at Amazon. Why you will love this opportunity: Despite being part of a large business, we embrace a start-up mentality. This is an opportunity for massive impact and affords a lot of autonomy. 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 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. Key job responsibilities As a Principal Applied Scientist on this team, you will: - Be the technical science leader on the org; leading efforts within the team and across other teams. - Perform hands-on analysis and modeling of enormous data sets to develop insights that increase traffic monetization and retail merchandise sales, without compromising the shopper experience. - Drive end-to-end Machine Learning projects that have a high degree of ambiguity, scale, complexity. - Build machine learning models, perform proof-of-concept, experiment, optimize, and deploy your models into production; work closely with software engineers to assist in productionizing your ML models. - Run A/B experiments, gather data, and perform statistical analysis. - Establish scalable, efficient, automated processes for large-scale data analysis, machine-learning model development, model validation and serving. - Research new and innovative machine learning approaches. - Recruit Applied Scientists to the team and provide mentorship. About the team Amazon Advertising operates at the intersection of eCommerce and advertising, offering a rich array of digital advertising solutions with the goal of helping our customers find and discover anything they want to buy. We help advertisers reach Amazon customers on some of the most valued advertising real estate on the internet on the Amazon.com store. We start with the customer and work backwards in everything we do, including advertising.

Are you inspired by invention? Is problem solving through teamwork in your DNA? Do you like the idea of seeing how your work impacts the bigger picture? Answer yes to any of these and you’ll fit right in here at Amazon Robotics. We are a smart team of doers who work passionately to apply cutting edge advances in robotics and software to solve real-world challenges that will transform our customers’ experiences. We invent new improvements every day. We are Amazon Robotics and we will give you the tools and support you need to invent with us in ways that are rewarding, fulfilling, and fun. Amazon Robotics empowers a smarter, faster, more consistent customer experience through automation. Amazon Robotics automates fulfillment center operations using various methods of robotic technology including autonomous mobile robots, sophisticated control software, language perception, power management, computer vision, depth sensing, machine learning, object recognition, and semantic understanding of commands. Amazon Robotics has a dedicated focus on research and development to continuously explore new opportunities to extend its product lines into new areas. Key job responsibilities We are seeking an enthusiastic Data Scientist to: - Design and implement state-of-the-art solutions for never-before-solved problems. - Collaborate closely with other research and robotics experts to design and run experiments, research new algorithms, and find new ways to improve Amazon Robotics analytics to optimize the Customer experience. - Partner with technology and product leaders to solve business problems using scientific approaches. - Build new tools and invent business insights that surprise and delight our customers. - Work to quantify system performance at scale, and to expand the breadth and depth of our analysis to increase the ability of software components and warehouse processes. - Work to evolve our library of key performance indicators and construct experiments that efficiently root cause emergent behaviors. - Engage with software development teams and warehouse design engineers to drive the evolution of the Amazon Robotics system, as well as the simulation engine that supports our work. A day in the life As a member of the Software Research and Data Science (SWRDS) team, there are multiple different paths you can take. For example, you may conduct deep dive analysis of both structured and unstructured robotics field analyses. Some of our team members focus on modeling, pipelines and tooling work, while others focus more on analytic work. We also have team members working on early-concept solution analysis (leveraging simulations, ML-based models, experimenting with new solutions). About the team The Amazon Robotics Software Research and Data Science (SWRDS) team builds and runs simulation experiments and delivers analyses that are central to understanding the performance of the entire Amazon Robotics system. This includes operational and software scaling characteristics, bottlenecks, and robustness to “chaos monkey” stresses -- we inform critical engineering and business decisions about Amazon’s approach to robotic fulfillment.

Amazon launched the Generative AI Innovation Center (GenAIIC) in June 2023 to help AWS customers accelerate the use of generative AI to solve business and operational problems and promote innovation in their organization. This is a team of strategists, data scientists, engineers, and solution architects working step-by-step with customers to build bespoke solutions that harness the power of generative AI.(https://press.aboutamazon.com/2023/6/aws-announces- generative-ai-innovation-center). We’re looking for Data Scientists capable of using generative AI and other techniques to design, evangelize, and implement state-of-the-art solutions for never-before-solved problems. You will work directly with customers and innovate in a fast-paced organization that contributes to game-changing projects and technologies. You will design and run experiments, research new algorithms, and find new ways of optimizing risk, profitability, and customer experience. Emirati national is required. Key job responsibilities As a Data Scientist, you will - Collaborate with AI/ML scientists, engineers, and architects to Research, design, develop, and evaluate cutting-edge generative AI algorithms to address real-world challenges - Interact with customers directly to understand the business problem, help and aid them in implementation of generative AI solutions, deliver briefing and deep dive sessions to customers and guide customer on adoption patterns and paths to production - Create and deliver best practice recommendations, tutorials, blog posts, sample code, and presentations adapted to technical, business, and executive stakeholder - Provide customer and market feedback to Product and Engineering teams to help define product direction About the team The team helps customers imagine and scope the use cases that will create the greatest value for their businesses, select and train or fine tune the right models, define paths to navigate technical or business challenges, develop proof-of-concepts, and make plans for launching solutions at scale. The Generative AI Innovation Center team provides guidance on best practices for applying generative AI responsibly and cost efficiently. Diverse Experiences AWS values diverse experiences. Even if you do not meet all of the qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying. Why AWS? Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that’s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses. Inclusive Team Culture Here at AWS, it’s in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences, inspire us to never stop embracing our uniqueness. Mentorship & Career Growth We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional. Work/Life Balance We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve in the cloud.

Do you want to join an innovative team of scientists who invent and apply the most advanced machine learning and NLP techniques to create the best customer engagement experience on the earth? Do you want to revolutionize the way how customers solve their issues and get their questions answered? At Customer Engagement Technology (CET), we develop peculiar products that help customers solve problems. We innovate on behalf of customers, developing Bot, self-service, and associate-facing products that delight customers and support our world class customer service workforce. We are looking for talented Postdoctoral Scientists to join our CET Machine Learning team in Seattle, WA for a one-year, full-time research position to work on research and development of task oriented dialogue agents for the customer support domain. We utilize Large Language Models (LLMs) to address challenges within TOD systems, such as Natural Language Generation for generating system responses based, state tracking, decision making etc. We publish our research in top tier NLP and AI venues (EMNLP, ACL, AAAI, etc), and deploy ML powered chatbots primarily in the customer returns domain. Key job responsibilities In this role you will: • Work closely with a senior science advisor, collaborate with other scientists and engineers, and be part of Amazon’s vibrant and diverse global science community. • Publish your innovation in top-tier academic venues and hone your presentation skills. • Be inspired by challenges and opportunities to invent cutting-edge techniques in your area(s) of expertise.

Are you a MS or PhD student interested in a 2025 Internship in Data Science? If so, we want to hear from you! We are looking for a customer obsessed Data Scientist Intern who can innovate in a business environment, building and deploying machine learning models to drive step-change innovation and scale it to the EU/worldwide. If this describes you, come and join our Data Science teams at Amazon for an exciting internship opportunity. If you are insatiably curious and always want to learn more, then you’ve come to the right place. You can find more information about the Amazon Science community as well as our interview process via the links below; https://www.amazon.science/ https://amazon.jobs/content/en/career-programs/university/science Emirati nationality is required. Key job responsibilities As a Data Science Intern, you will have following key job responsibilities: • Work closely with scientists and engineers to architect and develop new algorithms to implement scientific solutions for Amazon problems. • Work on an interdisciplinary team on customer-obsessed research • Experience Amazon's customer-focused culture • Create and Deliver Machine Learning projects that can be quickly applied starting locally and scaled to EU/worldwide • Build and deploy Machine Learning models using large data-sets and cloud technology. • Create and share with audiences of varying levels technical papers and presentations • Define metrics and design algorithms to estimate customer satisfaction and engagement A day in the life At Amazon, you will grow into the high impact, visionary person you know you’re ready to be. Every day will be filled with developing new skills and achieving personal growth. How often can you say that your work changes the world? At Amazon, you’ll say it often. Join us and define tomorrow. Some more benefits of an Amazon Science internship include; • All of our internships offer a competitive stipend/salary • Interns are paired with an experienced manager and mentor(s) • Interns receive invitations to different events such as intern program initiatives or site events • Interns can build their professional and personal network with other Amazon Scientists • Interns can potentially publish work at top tier conferences each year About the team Applicants will be reviewed on a rolling basis and are assigned to teams aligned with their research interests and experience prior to interviews. Start dates are available throughout the year and durations can vary in length from 3-6 months for full time internships. This role may available across multiple locations in the EMEA region. Please note these are not remote internships.

Do you want to transform millions of customer's experience of interacting with AWS products using artificial intelligence and machine learning? Do you want to see the impacts of your work moving the needles on the billions dollars of AWS business? Do you want to stay on the cutting edge of technology (e.g. Gen AI, graph neural network, reinforcement learning, and forecasting models) to build scalable ML products that help AWS grow? The AWS Product Analytics and Data Science (PANDAS) team is at the forefront of leveraging cutting-edge AI/ML technology and infrastructure to redefine how internal product teams interact with and derive insights from their data. Our vision is to use artificial intelligence and machine learning to enable AWS product teams and business leaders to drive product growth and create personalized, optimized, and simplified product experience. We strive to improve customers’ product experience, directly influence AWS’s top line and bottom line, and help AWS business leaders drive product growth. We want to be a centralized ML platform team that democratizes ML capabilities to AWS product teams and transform their product and customer experience. You will work cross-functionally, typically collaborating with several teams of scientists, data engineer, product managers, and business leaders (GM/VP) in order to influence the business and technical strategy for a complex, high-performance organization. You will also drive impactful, long-term choices on system architecture, spearhead a high-quality science and engineering culture, leading the science innovation and business impacts across the org. Key job responsibilities - Utilize state-of-the-art machine learning, deep learning, and statistical techniques to develop models that can predict/classify business outcomes, automate decision-making processes, and enhance user experiences. - Conduct comprehensive data analyses to extract insights, identify patterns, and inform model development, utilizing large and complex datasets from diverse sources. - Design, development, and evaluation of innovative models for predictive learning, ensuring high-quality standards are maintained. Drive the best science and engineering practices. - Establish scalable, efficient, automated processes for large scale data analyses, model development, model validation, and model implementation. - Monitor and assess the performance of deployed models, implementing continuous improvement strategies to adapt to changing data patterns and business requirements. - Work cross-functionally with data & software engineering teams to build model implementations and integrate successful models and algorithms in production systems at very large scale, focusing on scalability, efficiency, and performance. - Research and implement novel machine learning and statistical approaches that can contribute to state of the art science with publication A day in the life In your role as an applied scientist, you will play a pivotal role in shaping product development by working closely with product managers, software engineers, and designers to translate business objectives into actionable scientific projects. You will be instrumental in identifying and securing the necessary datasets in collaboration with data management teams. Your expertise will guide the selection and implementation of advanced statistical and machine learning methods, ensuring the development of robust models. These models will then be refined, tested, and deployed in production. You'll communicate your ML solution to stakeholders and product teams through effective verbal and written communication. About the team We are a team of scientists and engineers supporting AWS product leaders to make high impact decisions through sophisticated analytical frameworks, trusted data science methods, and scalable ML products. We came from diverse backgrounds from statistics, computer science, engineering, and business analytics. We specialized in the full end to end ML development process, including data ingestion, ETL, model development, and model deployment in production. We are supporting the data science needs across AWS EC2, Database & Analytics, and S3 teams using deep learning, graph neural network, forecasting, reinforcement learning, causal inference, etc. About AWS Diverse Experiences AWS 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. 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. This team is part of AWS Utility Computing: Utility Computing (UC) 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.

Amazon is looking for talented Postdoctoral Scientists to join our Amazon Robotics team for a one-year, full-time research position. The host team is developing novel approaches to mobile robot operation to carry a wide range of loads and perform different roles in Amazon logistics. These robots are used in automating material handling throughout the fulfillment and sortation processes. The team focuses in multi-robot coordination and planning, while developing cost-sensitive solutions. The postdoc is expected to develop novel control and planning algorithms for a fleet of agile robots, working closely with mechanical engineers. Experience with hands-on development and bring-up of robotic systems would be a significant contribution to team goals. Key job responsibilities • Work closely with a senior science advisor, collaborate with other scientists and engineers, and be part of Amazon’s vibrant and diverse global science community. • Publish your innovation in top-tier academic venues and hone your presentation skills. • Be inspired by challenges and opportunities to invent cutting-edge techniques in your area(s) of expertise. • Be comfortable with a fast-paced work with a lot of unknowns and hands-on engagement.

Interested in building something new? Join the Amazon Autos team on an exhilarating journey to redefine the vehicle shopping experience. This is an opportunity to be part of the Amazon's new business ventures. Our goal is to create innovative automotive discovery and shopping experiences on Amazon, providing customers with greater convenience and a wider selection. You'll work in a creative, fast-paced, and entrepreneurial environment at the center of Amazon's innovation. As a key member, you'll play a pivotal role in helping us achieve our mission. We are looking for a highly accomplished Applied Science professional drive our science strategy, foster a culture of data-driven decision-making, and drive impactful business outcomes through advanced state-of-the-art science methodologies. If you're enthusiastic about innovating and delivering exceptional shopping experiences to customers, thrive on new challenges, and excel at solving complex problems using top-notch ML models, LLM and GenAI techniques, then you're the perfect candidate for this role. Strong business acumen and interpersonal skills are a must, as you'll work closely with business owners to understand customer needs and design scalable solutions. Join us on this exhilarating journey and be part of redefining the vehicle shopping experience. Key job responsibilities As an Applied Scientist in Amazon Autos, you will: - Shape the roadmap and strategy for applying science to solve customer problems in the Amazon AutoStore domain. - Drive big picture innovations with clear roadmaps for intermediate delivery. - Apply your skills in areas such as deep learning and reinforcement learning while building scalable solutions for business problems. - Produce and deliver models that help build best-in-class customer experiences and build systems that allow us to deploy these models to production with low latency and high throughput. - Utilize your Generative AI, time series and predictive modeling skills, and creative problem-solving skills to drive new projects from ideation to implementation. - Interface with business customers, gathering requirements and delivering science solutions. - Collaborate with cross-functional teams, including software engineers, data scientists, and product managers, to define project requirements, establish success metrics, and deliver high-quality solutions. - Effectively communicate complicated machine learning concepts to multiple partners. - Research new and innovative machine learning approaches. A day in the life In this role, you will be part of a multidisciplinary team working on one of Amazon's newest business ventures. As a key member, you will collaborate closely with engineering, product, design, operations, and business development to bring innovative solutions to our customers. Your science expertise will be leveraged to research and deliver novel solutions to existing problems, explore emerging problem spaces, and create new knowledge. You will invent and apply state-of-the-art technologies, such as large language models, machine learning, natural language processing, and computer vision, to build next-generation solutions for Amazon. You'll publish papers, file patents, and work closely with engineers to bring your ideas to production. About the team This is a critical role for Amazon Autos team with a vision to create innovative automotive discovery and shopping experiences on Amazon, providing customers better convenience and more selection. We’re collaborating with other experienced teams at Amazon to define the future of how customers research and shop for cars online.

Amazon strives to be Earth's most customer-centric company where people can find and discover virtually anything they want to buy online. Amazon's evolution is driven by the spirit of innovation that is part of the company's DNA. Amazon Seller Services is looking for a Data Scientist to work hands on from concept to delivery on generative AI, statistical analysis, prescriptive and predictive analysis, and machine learning implementation projects. We are looking for a problem solver with strong analytical skills and a solid understanding of statistics & Machine learning algorithm as well as a practical understanding of collecting, assembling, cleaning and setting up disparate data from enterprise systems. Key job responsibilities Responsibilities: Ability to understand a business problem and the available data and identify what statistical or ML techniques can be applied to answer a business question Given a business problem, estimate solution feasibility and potential approaches based on available data Understand what data is available, where, and how to pull it together. Work with partner teams where needed to facilitate permissions and acquisition of required data Quickly prototype solutions and build models to test feasibility of solution approach Build statistical models/ ML models, train and test them to and drive towards the optimal level of model performance Improve existing processes with development and implementation of state of the art generative AI models Work with technology teams to integrate models by wrapping them as services that plug into Amazon's marketplace and fulfillment systems Work across the spectrum of reporting and data visualization, statistical modeling and supervised learning tools and techniques and apply the right level of solution to the right problem The problem set covers aspects of detecting fraud and abuse, improving performance, driving lift and adoption, recommend the right upsell to the right audience, cost saving, selection economics and several others.

Here at Amazon, we embrace our differences. We are committed to furthering our culture of diversity and inclusion of our teams within the organization. How do you get items to customers quickly, cost-effectively, and—most importantly—safely, in less than an hour? And how do you do it in a way that can scale? Our teams of hundreds of scientists, engineers, aerospace professionals, and futurists have been working hard to do just that! We are delivering to customers, and are excited for what’s to come. Check out more information about Prime Air on the About Amazon blog (https://www.aboutamazon.com/news/transportation/amazon-prime-air-delivery-drone-reveal-photos). If you are seeking an iterative environment where you can drive innovation, apply state-of-the-art technologies to solve real world delivery challenges, and provide benefits to customers, Prime Air is the place for you. Come work on the Amazon Prime Air Team! Our Prime Air Drone Flight Sciences High Fidelity Methods (HFM) team is looking for an outstanding research scientist (RS) to develop and verify our drone systems models and flight physics models. Our models are the backbone of every flight simulation performed within Prime Air and are a critical input to business decisions, aircraft design, system verification, and aircraft certification. The HFM team’s products enable the prediction of vehicle performance metrics including range, maneuverability, tracking error, and aircraft stability. They help us understand how vehicle design and operational decisions impact business metrics like customer reachability. They are a crucial element in the design of flight control algorithms and software testing. The accuracy and reliability of these models are critical to the success of Prime Air. Key job responsibilities The person in this role is responsible for owning the development, deployment, verification, and maintenance of simulation models from end-to-end. This includes the initial gathering of the downstream customer needs, identifying the most suitable modelling approach and level of fidelity, coordinating the generation of input data, training models, developing and maintaining software interfaces, and verifying the model accuracy. This person will also be responsible for determining the most suitable modeling approach for a given physical phenomena. They will need to have a basic understanding of the types of physics and systems to be modelled including electric powertrain components, guidance and navigation system (GNS) sensors, vehicle aerodynamics, propeller performance, multibody dynamics, and atmosphere physics. They will be responsible for designing experiments for generating data used to create and verify models. They will be responsible for validating the models by leveraging uncertainty quantification and statistical analyses.