Careers

Does the thought of improving one of the world’s most complex logistic systems inspire you? Is your passion to sift through hundreds of systems, processes, and data sources to solve the puzzle and identify the next big opportunity? Are you a creative big thinker who is passionate about using data to direct decision making and solve complex and large-scale challenges? Are you fascinated by the interactions between operations and strategy? Do you feel like your skills uniquely qualify you to bridge communication between teams with competing priorities? If so, then this position is for you! Come help Amazon create cutting-edge science-driven technologies for delivering packages to the doorstep of our customers! The Last Mile Routing & Planning organization builds the software, algorithms and tools that make the “magic” of home delivery happen: our flow, sort, dispatch and routing intelligence systems are responsible for the billions of daily decisions needed to plan and execute safe, efficient and frustration-free routes for drivers around the world. Our team supports deliveries (and pickups!) for Amazon Logistics, Same Day, Amazon Grocery, Lockers, and other new initiatives across the world. In this role, your main focus will be to build algorithms, synthesize information, identify business opportunities, provide research direction, provide data-driven insights and communicate business and technical requirements within the team and across stakeholder groups. You will partner closely with other scientists and engineers in a collegial environment with a clear path to business impact. We have an exciting portfolio of research areas including vehicle routing, planning for electric and autonomous vehicles, district and stops planning, ultra-fast deliveries, fleet planning, and forecasting solutions for different delivery programs leveraging the latest OR, ML, and Generative AI methods, at a global scale. We are actively looking to hire scientists to lead one or more of these problem spaces. Successful candidates will have a deep knowledge of Operations Research and/or Machine/Deep Learning methods, experience in applying these methods to large-scale business problems, the ability to map models into production-worthy code in Python or Java, the communication skills necessary to explain complex technical approaches to a variety of stakeholders and customers, and the excitement to take iterative approaches to tackle big research challenges. Mentorship & Career Growth We care about your career growth! Whether your goals are to explore new technologies, take on bigger opportunities, or get to the next level, we'll help you get there. Our business is growing fast and our people will grow with it. Key job responsibilities * Invent and design new solutions for scientifically-complex problem areas and identify opportunities for invention in existing or new business initiatives. * Successfully deliver large or critical solutions to complex problems in the support of medium-to-large business goals. * Influence the design of scientifically-complex software solutions or systems, for which you personally write significant parts of the critical scientific novelty. * Apply mathematical optimization techniques, and/or machine/Gen-AI learning models to design solution methodologies to be used by in-house decision support tools and software. * Research, prototype, simulate, and experiment with these models and participate in the production level deployment in Python or Java. * Make insightful contributions to teams' roadmaps, goals, priorities, and approach. * Actively engage with the internal and external scientific communities by publishing scientific articles and participating in research conferences.

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 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 (Austria, France, Germany, Ireland, Israel, Italy, Luxembourg, Netherlands, Poland, Romania, Spain and the UK). Please note these are not remote internships.

Amazon Japan Store Tech (JST) Science team serves as the core science division of JP Store Tech, with the vision to enable and accelerate the best-in-class CX through state-of-the-art machine learning technologies. This team owns the science vision definition, science roadmap planning, and science solution delivery in key business areas in Japan including Search, Customer Growth and Engagement, Personalization and Delivery. As an Applied Scientist, you will design, implement and deliver models on Amazon site, helping millions of customers every day to find quickly what they are looking for. You will propose innovation to build ML models trained on terabytes of product and traffic data, which are evaluated using both offline metrics as well as online metrics from A/B testing. You will then integrate these models into the production system that serves customers, closing the loop through data, modeling, application, and customer feedback. The chosen approaches for model architecture will balance business-defined performance metrics with the needs of millisecond response times. Key job responsibilities * Invent or adapt new scientific approaches, models or algorithms inspired and driven by customers’ needs and benefits at the project level. * Analyze data and identify the gaps in existing solutions, and propose innovative science solutions. * Contribute to research papers that are published at peer-reviewed internal and/or external venues, and contribute to the wider scientific community. * Working with teams worldwide on global projects. Your benefits include: * Working on a high-impact, high-visibility product, with your work improving the experience of millions of customers * The opportunity to use (and innovate) state-of-the-art ML methods to solve real-world problems with tangible customer impact * Being part of a growing team where you can influence the team's mission, direction, and how we achieve our goals

Amazon Advertising is one of Amazon's fastest growing and most profitable businesses. Amazon's advertising portfolio helps merchants, retail vendors, and brand owners succeed via native advertising, which grows incremental sales of their products sold through Amazon. The primary goals are to help shoppers discover new products they love, be the most efficient way for advertisers to meet their business objectives, and build a sustainable business that continuously innovates on behalf of customers. Our products and solutions are strategically important to enable our Retail and Marketplace businesses to drive long-term growth. We deliver billions of ad impressions and millions of clicks and break fresh ground in product and technical innovations every day! The Creative X team within Amazon Advertising aims to democratize access to high-quality creatives (image, video, copy) by building AI-driven solutions for advertisers. To accomplish this, we are investing in latent-diffusion models, large language models (LLM), computer vision (CV), and related ML methods. You will be part of a close-knit team of applied scientists and machine learning engineers, who are highly collaborative and at the top of their respective fields. We are looking for talented an Applied Scientist who is adept at a variety of skills, especially with latent diffusion models, large language models, or related foundational models that will accelerate our plans to generate high-quality creatives on behalf of advertisers. Every member of the team is expected to build customer (advertiser) facing features, contribute to the collaborative and innovative spirit within the team, and bring cutting-edge applied research to raise the bar within the team. As a Sr. Generative AI Applied Scientist on this team, you will: * Drive end-to-end GenAI projects that have a high degree of ambiguity, scale and 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. * Perform hands-on analysis and modeling of enormous data sets to develop insights that increase traffic monetization and merchandise sales, without compromising the shopper experience. * Establish scalable, efficient, automated processes for large-scale data analysis, machine-learning model development, model validation and serving. * Identify and action data collection and labelling in conjunction with team members. * Research new and innovative machine learning approaches. * Present results and explain methods to senior leadership. Key job responsibilities This role is focused on generating image/text and building the related foundational models for generative AI. You will develop core models that will be the foundational of the core advertising-facing tools that we are launching. You will conduct literature reviews to stay on the cutting edge of the field. You will regularly engage with product managers and technical program managers, who will partner with you to productize your work. A day in the life On a day-to-day basis, you will be doing your independent research and work to develop and deploy models, you will participate in sprint planning, collaborative sessions with your peers, and demo new models and share results with peers, other partner teams and leadership. About the team The team consists of applied scientists and machine learning engineers. We reside in the Creative X organization, which focuses on creating products for advertisers that will improve the quality of the creatives within Amazon Ads.

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.

At Amazon's Stores Foundational AI - M5 team, we're revolutionizing e-commerce through advanced Large Language Models (LLMs). Our models power various customer interactions across Amazon's platform, enhancing the traditional and conversational shopping experience at every turn. We're looking for an exceptional science leader to spearhead our AI innovation efforts. In this role, you'll lead a high-performing team of scientists, developing cutting-edge LLM technologies that directly impact customer experiences. You'll collaborate with cross-functional teams, identifying new AI opportunities and translating research into practical, scalable solutions. As a leader, you'll mentor team members, fostering a culture of excellence and continuous learning. Your ability to inspire and guide technical experts will be crucial in pushing the boundaries of AI-driven e-commerce. This position offers a unique opportunity to shape the future of online shopping, making a lasting impact on millions of customers worldwide. If you're passionate about emerging technology, driven by customer-centric innovation, and ready to make a significant industry impact, we want to hear from you. Join us in transforming the e-commerce landscape through the power of AI.

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.

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.

The Campaign Measurement & Optimization (CMO) organization is looking for a Senior Applied Scientist interested in solving one of the most challenging business problems in marketing measurement and developing cutting-edge ML model. Working with our team of data scientists, applied scientists, research scientists, and economists, this leader will help redefine scalable marketing measurement at Amazon and its subsidiaries. The Campaign Measurement & Optimization (CMO) organization’s mission is to be the most trusted source of measurement science solutions to drive marketing investment decisions across Amazon. The CMO team provides incrementality and efficiency measurement services to the marketing stakeholders across Amazon’s lines of business, including Stores, Prime Video, Amazon Devices, Alexa, Amazon Business, Amazon Music, Amazon Fresh, as well as subsidiaries including Audible, Ring, Whole Foods, and more. CMO applies industry leading deep learning based causal inference models to measure omni-channel effectiveness of marketing campaigns from these businesses worldwide. The impact and influence of the organization is tremendous, helping optimize spend decisions on a scale that exceeds many countries’ GDP. Our outputs shape Amazon product and marketing teams’ decisions and therefore how Amazon customers see, use, and value their experience with Amazon. This is a high-impact role with opportunities to develop systems and analyze marketing effectiveness that contributes billions of dollars to the business. As a senior scientist, you will be responsible for leading the design and development of the cutting edge measurement and optimization models, while collaborating with businesses, marketers, and software teams to solve key challenges facing the teams. Such challenges include measuring the incremental impact of multi-channel marketing portfolios, estimating the impact on sparse customer actions, and scaling measurement solutions for WW marketplaces. Unlike many companies who buy existing off-the-shelf marketing measurement systems, we are responsible for studying, designing, and building systems to serve Amazon’s suite of businesses. Our team members have an opportunity to be on the forefront of marketing measurement thought leadership by working on some of the most difficult problems in the industry with some of the best product managers, scientists, economists and software developers in the business. In this role, you will be a technical leader in applied science research with significant scope, impact, and high visibility. You will lead strategic measurement science initiatives in CMO and across various marketing teams, scaling experimentation and development and deployment of the measurement science models, real-time inference, and cross-channel orchestration. As a successful Scientist, you are an analytical problem solver who enjoys diving into data, leads problem solving, guides development of new frameworks, writes code, is excited about investigations and algorithms, and can credibly interface between technical teams and business stakeholders. You are an expert in employing deep learning models to solve business problems, preferably in causal inference. You are a hands-on innovator who can contribute to advancing Marketing measurement technology in a B2C and B2B environment, and push the limits on what’s scientifically possible with a razor sharp focus on measurable customer and business impact. You will also coach and guide scientists in the team to grow the team’s talent and scale the impact of your work.

The Campaign Measurement & Optimization (CMO) organization is looking for a Senior Economist interested in solving one of the most challenging business problems in marketing measurement and developing cutting-edge ML model. Working with our team of data scientists, applied scientists, research scientists, and economists, this leader will help redefine scalable marketing measurement at Amazon and its subsidiaries. The Campaign Measurement & Optimization (CMO) organization’s mission is to be the most trusted source of measurement science solutions to drive marketing investment decisions across Amazon. The CMO team provides incrementality and efficiency measurement services to the marketing stakeholders across Amazon’s lines of business, including Stores, Prime Video, Amazon Devices, Alexa, Amazon Business, Amazon Music, Amazon Fresh, as well as subsidiaries including Audible, Ring, Whole Foods, and more. CMO applies industry leading deep learning based causal inference models to measure omni-channel effectiveness of marketing campaigns from these businesses worldwide. The impact and influence of the organization is tremendous, helping optimize spend decisions on a scale that exceeds many countries’ GDP. Our outputs shape Amazon product and marketing teams’ decisions and therefore how Amazon customers see, use, and value their experience with Amazon. This is a high-impact role with opportunities to develop systems and analyze marketing effectiveness that contributes billions of dollars to the business. As a senior Economist, you will be responsible for leading the design and development of the cutting edge measurement and optimization models, while collaborating with businesses, marketers, and software teams to solve key challenges facing the teams. Such challenges include measuring the incremental impact of multi-channel marketing portfolios, estimating the impact on sparse customer actions, and scaling measurement solutions for WW marketplaces. Unlike many companies who buy existing off-the-shelf marketing measurement systems, we are responsible for studying, designing, and building systems to serve Amazon’s suite of businesses. Our team members have an opportunity to be on the forefront of marketing measurement thought leadership by working on some of the most difficult problems in the industry with some of the best product managers, scientists, economists and software developers in the business. In this role, you will be a technical leader in Econometric research with significant scope, impact, and high visibility. You will lead strategic measurement science initiatives in CMO and across various marketing teams, scaling experimentation and development and deployment of the measurement science models, real-time inference, and cross-channel orchestration. As a successful Economist, you are an analytical problem solver who enjoys diving into data, leads problem solving, guides development of new frameworks, writes code, is excited about investigations and algorithms, and can credibly interface between technical teams and business stakeholders. You are an expert in causal inference models to solve business problems. You are a hands-on innovator who can contribute to advancing Marketing measurement technology in a B2C and B2B environment, and push the limits on what’s scientifically possible with a razor sharp focus on measurable customer and business impact. You will also coach and guide scientists in the team to grow the team’s talent and scale the impact of your work.