Careers

Interested to build the next generation Financial systems that can handle billions of dollars in transactions? Interested to build highly scalable next generation systems that could utilize Amazon Cloud? Massive data volume + complex business rules in a highly distributed and service oriented architecture, a world class information collection and delivery challenge. Our challenge is to deliver the software systems which accurately capture, process, and report on the huge volume of financial transactions that are generated each day as millions of customers make purchases, as thousands of Vendors and Partners are paid, as inventory moves in and out of warehouses, as commissions are calculated, and as taxes are collected in hundreds of jurisdictions worldwide. Key job responsibilities • Understand the business and discover actionable insights from large volumes of data through application of machine learning, statistics or causal inference. • Analyse and extract relevant information from large amounts of Amazon’s historical transactions data to help automate and optimize key processes • Research, develop and implement novel machine learning and statistical approaches for anomaly, theft, fraud, abusive and wasteful transactions detection. • Use machine learning and analytical techniques to create scalable solutions for business problems. • Identify new areas where machine learning can be applied for solving business problems. • Partner with developers and business teams to put your models in production. • Mentor other scientists and engineers in the use of ML techniques. A day in the life • Understand the business and discover actionable insights from large volumes of data through application of machine learning, statistics or causal inference. • Analyse and extract relevant information from large amounts of Amazon’s historical transactions data to help automate and optimize key processes • Research, develop and implement novel machine learning and statistical approaches for anomaly, theft, fraud, abusive and wasteful transactions detection. • Use machine learning and analytical techniques to create scalable solutions for business problems. • Identify new areas where machine learning can be applied for solving business problems. • Partner with developers and business teams to put your models in production. • Mentor other scientists and engineers in the use of ML techniques. About the team The FinAuto TFAW(theft, fraud, abuse, waste) team is part of FGBS Org and focuses on building applications utilizing machine learning models to identify and prevent theft, fraud, abusive and wasteful(TFAW) financial transactions across Amazon. Our mission is to prevent every single TFAW transaction. As a Machine Learning Scientist in the team, you will be driving the TFAW Sciences roadmap, conduct research to develop state-of-the-art solutions through a combination of data mining, statistical and machine learning techniques, and coordinate with Engineering team to put these models into production. You will need to collaborate effectively with internal stakeholders, cross-functional teams to solve problems, create operational efficiencies, and deliver successfully against high organizational standards.

As part of the AWS Solutions organization, we have a vision to provide business applications, leveraging Amazon’s unique experience and expertise, that are used by millions of companies worldwide to manage day-to-day operations. We will accomplish this by accelerating our customers’ businesses through delivery of intuitive and differentiated technology solutions that solve enduring business challenges. We blend vision with curiosity and Amazon’s real-world experience to build opinionated, turnkey solutions. Where customers prefer to buy over build, we become their trusted partner with solutions that are no-brainers to buy and easy to use. The Team Our research team is tackling fundamental challenges in visual reasoning that combine generative AI and agentic frameworks. We're investigating novel approaches to how AI systems understand spatial relationships, reason about object interactions, and maintain contextual awareness across time. Working at the intersection of computer vision and large language models, we're developing theoretical frameworks and practical techniques that advance the state-of-the-art in visual AI. As part of the AWS Applied AI Solutions organization, we’re advancing the frontier of visual reasoning and agentic AI technologies. Our vision is to develop sophisticated AI systems that can understand, interpret, and reason about visual information at human-like levels, enabling breakthrough applications across multiple industries. Key job responsibilities Everyone on the team needs to be entrepreneurial, wear many hats and work in a highly collaborative environment that’s more startup than big company. We’ll need to tackle problems that span a variety of domains: computer vision, image recognition, machine learning, real-time and distributed systems. As an Applied Scientist, you will help solve a variety of technical challenges and mentor other scientists. You will tackle challenging, novel situations every day and given the size of this initiative, you’ll have the opportunity to work with multiple technical teams at Amazon in different locations. You should be comfortable with a degree of ambiguity that’s higher than most projects and relish the idea of solving problems that, frankly, haven’t been solved at scale before - anywhere. Along the way, we guarantee that you’ll learn a ton, have fun and make a positive impact on millions of people. A key focus of this role will be developing and implementing advanced visual reasoning systems that can understand complex spatial relationships and object interactions in real-time. You'll work on designing autonomous AI agents that can make intelligent decisions based on visual inputs, understand customer behavior patterns, and adapt to dynamic retail environments. This includes developing systems that can perform complex scene understanding, reason about object permanence, and predict customer intentions through visual cues. About the team AWS Solutions As part of the AWS solutions organization, we have a vision to provide business applications, leveraging Amazon's unique experience and expertise, that are used by millions of companies worldwide to manage day-to-day operations. We will accomplish this by accelerating our customers' businesses through delivery of intuitive and differentiated technology solutions that solve enduring business challenges. we blend vision with curiosity and Amazon's real-world experience to build opinionated, turnkey solutions. Where customers prefer to buy over build, we become their trusted partner with solutions that are no-brainers to buy and easy to use. 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 AWS values curiosity and connection. Our employee-led and company-sponsored affinity groups promote inclusion and empower our people to take pride in what makes us unique. Our inclusion events foster stronger, more collaborative teams. Our continual innovation is fueled by the bold ideas, fresh perspectives, and passionate voices our teams bring to everything we do. 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.

Are you passionate about building data-driven applied science solutions to drive the profitability of the business? Are you excited about solving complex real world problems? Do you have proven analytical capabilities, exceptional communication, project management skills, and the ability to multi-task and thrive in a fast-paced environment? Join us an Applied Scientist to deliver applied science solutions for Amazon Payment Products. Amazon Payment Products team creates and manages a global portfolio of payment products, including co-branded credit cards, installment financing, etc. Within this team, we are looking for an Applied Scientist who will be responsible for the following: Key job responsibilities As an Applied Scientist, you will be responsible for designing and deploying scalable ML, GenAI, Agentic AI solutions that will impact the payments of millions of customers and solve key customer experience issues. You will develop novel deep learning, LLM for task automation, text processing, pattern recognition, and anomaly detection problems. You will define the research and experiments strategy with an iterative execution approach to develop AI/ML models and progressively improve the results over time. You will partner with business and engineering teams to identify and solve large and complex problems that require scientific innovation. You will help the team leverage your expertise, by coaching and mentoring. You will contribute to the professional development of colleagues, improving their technical knowledge and the engineering practices. You will independently as well as guide team to file for patents and/or publish research work where opportunities arise. As the Payment Products organization deals with problems that are directly related to payments of customers, the Applied Scientist role will impact the large product strategy, identify new business opportunities and provides strategic direction, which will be very exciting.

The Marketing Measurement & Performance Support (MAPS) organization is looking for a Science Manager, interested in leading a team of Economists, Data Scientists and Applied Scientists in designing a measurement system to solve one of the most challenging business problems in marketing measurement. This exceptional leader will develop solutions combining experimental evidence, observational models and decision frameworks to redefine brand marketing measurement. The MAPS organization’s mission is to be the most trusted source of measurement science solutions to drive marketing investment decisions across Amazon. The MAPS team provides incrementality, efficiency measurement services and decision support to marketing stakeholders across Amazon’s Stores suit of businesses. MAPS applies industry leading causal inference models and designs experiments to measure omni-channel effectiveness of marketing campaigns from these businesses worldwide. Our outputs shape Amazon product and marketing teams’ decisions and therefore how Amazon customers see, use, and value their experience with Amazon. As a Science Manager, you will lead a team of scientists to develop state-of-the-art models, while collaborating with other scientists, 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 long term inter-related 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. Key job responsibilities In this role, you will be a people manager and a technical leader in Econometric research with significant scope, impact, and high visibility. You will own developing the next generation of Causal Marketing-Mix-Media (MMM) models combining experimental evidence with observational econometric techniques. Your solution will deliver to business leaders accurate and actionable incrementality estimates and recommendations to optimize their marketing portfolio. As a successful Science Manager, you can navigate ambiguity, lead problem solving, guide development of new frameworks, and credibly interface between technical teams and business stakeholders. You are an innovator who can push the limits on what’s scientifically possible with a razor sharp focus on measurable business impact. You will coach and guide scientists in your team across different job families including Economists, Data Scientists and Applied Scientists to grow the team’s talent and scale the impact of your work.

We are looking for a Principal Applied Scientist to drive technical innovation in visual reasoning systems across multiple domains. You will be a technical leader who sets the research direction, architects novel solutions, and delivers breakthrough results that advance the state of the art while solving real-world business problems. You will be leading the efforts of building a next-generation visual reasoning engine powered by frontier Large Video Models (LVMs). Your mission is to build a system that rivals human understanding of the physical world — moving far beyond the static perception of detection and tracking into the realm of deep spatial-temporal reasoning. This is not a passive computer vision tool; it is an agentic collaborator capable of interpreting natural language instructions, navigating unstructured environments, and executing complex tasks. You will sit at the high-stakes intersection of LVMs, LLMs, and Agentic AI, engineering systems that don't just 'see' but reason and act within the physical world. You will own end-to-end technical solutions from research to production deployment, driving innovation through hands-on research, prototyping, and deployment while delivering production impact. Key job responsibilities * Direct the technical vision for next-gen visual reasoning, pioneering the use of LVMs to solve high-dimensional spatial-temporal problems * Designing and implementing novel algorithms that push the boundaries of what's possible with generative AI * Architecting scalable solutions that deliver real-time insights across diverse environments * Building agentic AI systems that autonomously execute end-to-end workflows, transforming visual data into actionable business intelligence * Leading cross-functional collaboration to translate research breakthroughs into production systems * Publishing research at top-tier conferences (CVPR, NeurIPS, ICML) and establishing technical thought leadership in visual reasoning and multi-modal AI * Mentoring scientists and engineers to elevate technical excellence across the organization * Influencing product roadmaps through deep technical expertise and business acumen About the team Just Walk Out (JWO) is a checkout-free shopping experience where customers simply enter the store, take what they want, and leave—no lines, no scanning, no checkout. Our Just Walk Out Technology automatically detects when products are taken from or returned to the shelves, keeps track of them in a virtual cart, and charges customers' accounts after they leave. Check it out at https://www.justwalkout.com/. Designed and custom-built by Amazonians, our Just Walk Out Technology uses cutting-edge visual reasoning systems powered by vision-language-reasoning models to understand complex shopping behaviors in real-time. Our algorithms process multi-camera video streams to track customers throughout their shopping journey and determine exactly what items customers take—all without requiring them to scan or checkout. Innovation is part of our DNA! We are now applying our visual reasoning expertise to solve critical challenges in new domains beyond retail. We need people who want to join an ambitious program to expand beyond retail, building state-of-the-art visual reasoning systems that work across domains in physical AI. This expansion represents a significant opportunity to apply cutting-edge vision-language models, multi-modal AI, and generative AI technologies to enterprise applications with massive business impact, enabling automated decision-making capabilities.

Are you inspired by the power of Large Language Models (LLM) to transform the way we interact with technology? Are you fascinated by the use of Generative AI to build an advertiser facing solution that predict problems and coach users while they solve real word problems? Are you passionate about applying advanced machine learning techniques to solve complex challenges in the customer service space? If so, Amazon Advertising's Support Product & Services (SP&S) team has an exciting opportunity for you as an Applied Scientist. Key job responsibilities • Apply your expertise in LLM models to design, develop, and implement scalable machine learning solutions that address complex language-related challenges in the advertising support center domain. • Use Transformers and apply other NLP techniques like Sentence embeddings, Dimensionality reduction, clustering and topic modeling to identify customer intents and utterances. • Use services like AWS Lex, AWS Bedrock etc. to develop advertising facing solutions • Work closely with teams of scientists and software engineers to drive real-time model implementations and deliver novel and highly impactful solutions. • Automating feedback loops for algorithms in production. • Setup and monitor alarms to detect anomalous data patterns and perform root cause analyses to explain and address them. • Be a member of the Amazon-wide Machine Learning Community, participating in internal and external MeetUps, Hackathons and Conferences. A day in the life You will work closely with a cross functional team of Software Engineers, Product Owners, Data Scientists, and Contact Center experts. You will research and investigate the latest options in industry to apply machine learning and generative AI to real world problems. You will work backwards from customer problems and collaborate with stakeholders to determine how to scale new technology and integrate with complicated help channels used by advertisers everyday. About the team SP&S team provides solutions and libraries that are leveraged by teams all across Amazon Advertising to provide timely and personalized help. The team aims to predict Advertisers problems and proactively surface intelligent guidance to customers at the right time. As a AS, you will help the team to achieve its vision of building and implementing the next generation of Contact Center technology. You will build/leverage LLMs to train them on advertising support domain knowledge and work shoulder to shoulder with stakeholders to externalize to users in novel ways.

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. We are seeking a highly skilled and analytical Research Scientist. You will play an integral part in the measurement and optimization of Amazon Music marketing activities. You will have the opportunity to work with a rich marketing dataset together with the marketing managers. This role will focus on developing and implementing causal models and randomized controlled trials to assess marketing effectiveness and inform strategic decision-making. This role is suitable for candidates with strong background in causal inference, statistical analysis, and data-driven problem-solving, with the ability to translate complex data into actionable insights. As a key member of our team, you will work closely with cross-functional partners to optimize marketing strategies and drive business growth. Key job responsibilities Develop Causal Models Design, build, and validate causal models to evaluate the impact of marketing campaigns and initiatives. Leverage advanced statistical methods to identify and quantify causal relationships. Conduct Randomized Controlled Trials Design and implement randomized controlled trials (RCTs) to rigorously test the effectiveness of marketing strategies. Ensure robust experimental design and proper execution to derive credible insights. Statistical Analysis and Inference Perform complex statistical analyses to interpret data from experiments and observational studies. Use statistical software and programming languages to analyze large datasets and extract meaningful patterns. Data-Driven Decision Making Collaborate with marketing teams to provide data-driven recommendations that enhance campaign performance and ROI. Present findings and insights to stakeholders in a clear and actionable manner. Collaborative Problem Solving Work closely with cross-functional teams, including marketing, product, and engineering, to identify key business questions and develop analytical solutions. Foster a culture of data-informed decision-making across the organization. Stay Current with Industry Trends Keep abreast of the latest developments in data science, causal inference, and marketing analytics. Apply new methodologies and technologies to improve the accuracy and efficiency of marketing measurement. Documentation and Reporting Maintain comprehensive documentation of models, experiments, and analytical processes. Prepare reports and presentations that effectively communicate complex analyses to non-technical audiences.

Join our Amazon Private Brands Selection Guidance organization in building science and tech solutions at scale to delight our customers with products across our leading private brands such as Amazon Basics, Amazon Essentials, and by Amazon. The Selection Guidance team applies Generative AI, Machine Learning, Statistics, and Economics solutions to drive our private brands product assortment, strategic business decisions, and product inputs such as title, price, merchandising and ordering. We are an interdisciplinary team of Scientists, Economists, Engineers, and Product Managers incubating and building day one solutions using novel technology, to solve some of the toughest business problems at Amazon. As a Data Scientist you will investigate business problems using data, invent novel solutions and prototypes, and directly contribute to bringing your ideas to life through production implementation. Current research areas include named entity recognition, product substitutes, pricing optimization, agentic AI, and large language models. You will review and guide scientists across the team on their designs and implementations, and raise the team bar for science research and prototypes. This is a unique, high visibility opportunity for someone who wants to develop ambitious science solutions and have direct business and customer impact. Key job responsibilities - Partner with business stakeholders to deeply understand APB business problems and frame ambiguous business problems as science problems and solutions. - Perform data analysis and build data pipelines to drive business decisions. - Invent novel science solutions, develop prototypes, and deploy production software to solve business problems. - Review and guide science solutions across the team. - Publish and socialize your and the team's research across Amazon and external avenues as appropriate - Leverage industry best practices to establish repeatable applied science practices, principles & processes.

The Next Generation Developer Experience (NGDE) Science team is looking for an Applied Scientist who is passionate about building services and tools for developers that leverage artificial intelligence (AI) and machine learning (ML). You will be part of a team building AI-based services for Amazon Q Developer with the focus on redefining the way developer work. The team works in close collaboration with other AWS AI services such as AWS Bedrock, the AWS IDE Toolkit, and Amazon Sagemaker. If you are excited about working in cloud computing and building new AWS services, then we'd love to talk to you. Key job responsibilities As an Applied Scientist, you are recognized for your expertise, advise team members on a range of machine learning topics, and work closely with software engineers to drive the delivery of end-to-end modeling solutions. Your work focuses on ambiguous problem areas where the business problem or opportunity may not yet be defined. The problems that you take on require scientific breakthroughs. A day in the life 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. 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. About the team The Amazon Web Services (AWS) Next Gen DevX (NGDE) team is building Amazon Q for Developers to re-imagine all aspects of how builders create applications. We build AI products that are deployed in the IDE, the AWS console, and in web-based tools and services. We provide developers with AI assistants to generate code, features, and entire applications as well as to interact with AWS. We explore new technologies and find creative solutions, produce original research and bring cutting edge innovation to our customers. Curiosity and an explorative mindset can find a place here to impact the life of engineers around the world. If you are excited about this space, this is the team for you.

Our customers have immense faith in our ability to deliver packages timely and as expected. A well planned network seamlessly scales to handle millions of package movements a day. It has monitoring mechanisms that detect failures before they even happen (such as predicting network congestion, operations breakdown), and perform proactive corrective actions. When failures do happen, it has inbuilt redundancies to mitigate impact (such as determine other routes or service providers that can handle the extra load), and avoids relying on single points of failure (service provider, node, or arc). Finally, it is cost optimal, so that customers can be passed the benefit from an efficiently set up network. Amazon Shipping is hiring Applied Scientists to help improve our ability to plan and execute package movements. As an Applied Scientist in Amazon Shipping, you will work on multiple challenging machine learning problems spread across a wide spectrum of business problems. You will build ML models to help our transportation cost auditing platforms effectively audit off-manifest (discrepancies between planned and actual shipping cost). You will build models to improve the quality of financial and planning data by accurately predicting ship cost at a package level. Your models will help forecast the packages required to be pick from shipper warehouses to reduce First Mile shipping cost. Using signals from within the transportation network (such as network load, and velocity of movements derived from package scan events) and outside (such as weather signals), you will build models that predict delivery delay for every package. These models will help improve buyer experience by triggering early corrective actions, and generating proactive customer notifications. Your role will require you to demonstrate Think Big and Invent and Simplify, by refining and translating Transportation domain-related business problems into one or more Machine Learning problems. You will use techniques from a wide array of machine learning paradigms, such as supervised, unsupervised, semi-supervised and reinforcement learning. Your model choices will include, but not be limited to, linear/logistic models, tree based models, deep learning models, ensemble models, and Q-learning models. You will use techniques such as LIME and SHAP to make your models interpretable for your customers. You will employ a family of reusable modelling solutions to ensure that your ML solution scales across multiple regions (such as North America, Europe, Asia) and package movement types (such as small parcel movements and truck movements). You will partner with Applied Scientists and Research Scientists from other teams in US and India working on related business domains. Your models are expected to be of production quality, and will be directly used in production services. You will work as part of a diverse data science and engineering team comprising of other Applied Scientists, Software Development Engineers and Business Intelligence Engineers. You will participate in the Amazon ML community by authoring scientific papers and submitting them to Machine Learning conferences. You will mentor Applied Scientists and Software Development Engineers having a strong interest in ML. You will also be called upon to provide ML consultation outside your team for other problem statements. If you are excited by this charter, come join us!