Careers

Join us at Amazon as we reinvent shopping again! We're not just talking about improving the existing Amazon shopping experiences, we're building a brand-new world where shopping is effortless and intuitive through the power of generative AI. Leveraging state-of-the-art Large Language Models and generative AI, we're creating a live, two-way natural language conversational experience that is fast, helpful and trustworthy. As people turn to Amazon for deeper insights and understanding about products earlier and earlier in their shopping journeys, we're stepping up to the challenge by synthesizing complex information and multiple perspectives so customers can explore Amazon’s vast catalog to find exactly the products that solve their particular needs. Imagine having a back and forth conversation with an AI assistant helping you to articulate a problem you’re trying solve, effortlessly answering your product questions and giving you trustworthy advice and recommendations for what to buy. Also imagine a world where this same AI assistant reduces your mental load by proactively predicting and then fulfilling your shopping needs without you needing to interfere, thus saving you time and money along the way. We are building such an AI assistant to become the digital manifestation of the helpful salesperson that asks customers what they need, helps them navigate the store, waits unobtrusively while they look over the shelves, and helps them find complementary goods. What does economics have to teach this salesperson? Can we embed lessons from the behavioral literature to help customers? This is an opportunity to embed economic expertise into large scale generative models. This is just the beginning, and the future is yours to shape. We're searching for pioneers who are passionate about using technology and innovation to fundamentally change how customers shop, and who are ready to make a lasting impact on the industry and even disrupting how Amazon serves customers. You'll be a senior technical leader working with talented scientists, economists, engineers, and product leaders to innovate on behalf of our customers and help turn generative AI shopping into Amazon’s next business pillar. Key job responsibilities As the Principal Economist in the Shopping Economics team, you are a senior member of the technical leadership team, working with executives, principal engineers and scietists, and senior product leaders. Your economic thought leadership helps us to build new-to-world customer experiences that solve important problems for customers while creating new business models, ensuring Amazon is optimizing its innovation portfolio to maximally help customers solve their shopping problems. Solving problems like improving the match quality between customers’ heterogeneous needs and Amazon’s nearly infinite selection, articulating the economics of advertising in a conversation, using insights from economics to better align the LLM, and using deep learning techniques to measure substitution patterns and the economic value of engagement. You work with economists, scientists, and engineers Amazon-wide to rethink systems across the company to better optimize for helping customers through their entire shopping journey. You also develop and evangelize new mental models and new ways to measure the economic value of bleeding edge generative AI. As the senior economist in the team, you also guide the work and careers of other economists on the team.

Amazon Devices is revolutionizing smart home devices and services, and we're seeking a visionary Senior Economist to lead the charge. In this high-impact role, you'll flex your advanced Empirical IO and Structural Demand modeling expertise to tackle complex pricing challenges for a diverse portfolio of world-class products and services. Imagine being the driving force behind the pricing and demand strategies that power game-changing innovations for brands like Alexa, Ring, Blink, and Kids+. Your insights will directly influence critical business decisions, like optimizing, bundled offerings, and feature roadmaps for subscriptions. Get ready to dive deep, uncover valuable insights, and transform them into real-world impact. Whether you're supporting products pre-launch or fine-tuning mature business lines, your work will have a multi-million-dollar influence. As a Senior Economist on the Subscription Science team, you'll collaborate cross-functionally to shape product roadmaps. Sound like the kind of challenge you thrive on? Bring your passion for problem-solving, your knack for translating data into action, and your entrepreneurial spirit – and join us on the frontlines of the connected home revolution. This is your opportunity to make a lasting mark and create experiences that delight customers worldwide. Key job responsibilities - Develop advanced structural demand and econometric frameworks for products and services in Amazon Devices. - Create and drive the scientific roadmap for the team, and influence partner science teams - Drive cross-functional collaboration with scientists, engineers, and business leaders to integrate economic insights into strategic decision-making processes and shape future initiatives. - Communicate insights in writing and verbally, to senior leaders on Product and Finance teams within the company. - Actively mentor junior scientists on advanced econometric techniques. About the team This role is in the Subscription Science team, a cross-functional team in Amazon Devices that focuses on developing science models to inform major one-way door decisions that lead to customer facing changes for our products and services, and using these insights to help product teams focus efforts on improving products for their customers. We do this by building world-class demand models which provide pricing recommendations, for these organizations and help inform critical business investment decisions, frequently presenting results to the highest levels of leadership in the organization. In addition to the primary job location we are open to considering locations near major Amazon hubs including but not limited to Arlington VA (HQ2 near DC).

Our mission is to create best-in-class AI agents that seamlessly integrate multimodal inputs like speech, images, and video, enabling natural, empathetic, and adaptive interactions. We develop cutting-edge Large Language Models (LLMs) that leverage advanced architectures, cross-modal learning, interpretability, and responsible AI techniques to provide coherent, context-aware responses augmented by real-time knowledge retrieval. We seek a talented Applied Scientist with expertise in LLMs, speech, audio, NLP, or multimodal learning to pioneer innovations in data simulation, representation, model pre-training/fine-tuning, generation, reasoning, retrieval, and evaluation. The ideal candidate will build scalable solutions for a variety of applications, such as streaming real-time conversational experiences, including multilingual support, talking avatar interactions, customizable personalities, and conversational turn-taking. With a passion for pushing boundaries and rapid experimentation, you'll deliver high-impact solutions from research to customer-facing products and services. Key job responsibilities As an Applied Scientist, you'll leverage your expertise to research novel algorithms and modeling techniques to develop data simulation approaches mimicking real-world interactions with a focus on the speech modality. You'll acquire and curate large, diverse datasets while ensuring privacy, creating robust evaluation metrics and test sets to comprehensively assess LLM performance. Integrating human-in-the-loop feedback, you'll iterate on data selection, sampling, and enhancement techniques to improve the core model performance. Your innovations in data representation, model pre-training/fine-tuning on simulated and real-world datasets, and responsible AI practices will directly impact customers through new AI products and services.

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 is seeking students to join us for a 5-6 month internship (full-time, 40 hours per week) as Data Science Co-op. Please note that by applying to this role you would be considered for Data Scientist spring co-op and fall co-op roles on various Amazon Robotics teams. The internship/co-op project(s) and location are determined by the team the student will be working on. Learn more about Amazon Robotics: https://amazon.jobs/en/teams/amazon-robotics About the team Amazon 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.

AWS Resilience owns service to prevent and response to availability and security issues for all AWS Services. In other words, we’re the people who keep the cloud running. We work on the most challenging problems, with constant new services and possible failure modes to prevent — and we’re looking for talented people who want to help. You’ll join a diverse team of software, security experts, operations managers, and other vital roles. You’ll collaborate with people across AWS to help us deliver the highest standards for safety and security and availability. You’ll experience an inclusive culture that welcomes bold ideas and empowers you to own them to completion. AWS Incident Response is at the heart of the high availability of Amazon Web Services. We make customer impacting events shorter and less frequent by driving large scale event and incident response. Our automated tooling quickly identifies the cause of an issue and helps mitigate its impact, and much of our engineer time is spent on projects to improve the tooling and automation. We also provide manual incident management for AWS and other Amazon groups, directing the resolution of an issue with service teams, and diving deep into those events to drive improvements to the tooling. It's an exciting time to join our team as we are growing and expanding our offerings. Key job responsibilities You will own the organisation strategy relative to the usage of ML, GenAI and propose the best technology to advance our ability to better detect, faster root cause ,and correlate to prior incidents to shorten customer facing AWS incidents. Your work will enable us to identify gaps in our current strategy, learnings from past incidents. You will contribute to shortening incident response through deep analysis and introduction of new technology. About the team AWS Infrastructure Services (AIS) AWS Infrastructure Services owns the design, planning, delivery, and operation of all AWS global infrastructure. In other words, we’re the people who keep the cloud running. We support all AWS data centers and all of the servers, storage, networking, power, and cooling equipment that ensure our customers have continual access to the innovation they rely on. We work on the most challenging problems, with thousands of variables impacting the supply chain — and we’re looking for talented people who want to help. You’ll join a diverse team of software, hardware, and network engineers, supply chain specialists, security experts, operations managers, and other vital roles. You’ll collaborate with people across AWS to help us deliver the highest standards for safety and security while providing seemingly infinite capacity at the lowest possible cost for our customers. And you’ll experience an inclusive culture that welcomes bold ideas and empowers you to own them to completion. 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.

Do you want to join an innovative team of scientists who use deep learning, natural language processing, large language models to help Amazon provide the best seller experience across the entire Seller life cycle, including recruitment, growth, support and provide the best customer and seller experience by automatically mitigating risk? Do you want to build advanced algorithmic systems that help manage the trust and safety of millions of customer interactions every day? Are you excited by the prospect of analyzing and modeling terabytes of data and creating state-of-the-art algorithms to solve real world problems? Are you excited by the opportunity to leverage GenAI and innovate on top of the state-of-the-art large language models to improve customer and seller experience? Do you like to build end-to-end business solutions and directly impact the profitability of the company? Do you like to innovate and simplify processes? If yes, then you may be a great fit to join the Machine Learning Accelerator team in the Amazon Selling Partner Services (SPS) group. Key job responsibilities The scope of an Applied Scientist III in the Selling Partner Services (SPS) Machine Learning Accelerator (MLA) team is to research and prototype Machine Learning applications that solve strategic business problems across SPS domains. Additionally, the scientist collaborates with engineers and business partners to design and implement solutions at scale when they are determined to be of broad benefit to SPS organizations. They develop large-scale solutions for high impact projects, introduce tools and other techniques that can be used to solve problems from various perspectives, and show depth and competence in more than one area. They influence the team’s technical strategy by making insightful contributions to the team’s priorities, approach and planning. They develop and introduce tools and practices that streamline the work of the team, and they mentor junior team members and participate in hiring.

We’re working to improve shopping on Amazon using the conversational capabilities of large language models, and are searching for pioneers who are passionate about technology, innovation, and customer experience, and are ready to make a lasting impact on the industry. You'll be working with talented scientists, engineers, and technical program managers (TPM) to innovate on behalf of our customers. If you're fired up about being part of a dynamic, driven team, then this is your moment to join us on this exciting journey! Key job responsibilities We seek strong Applied Scientists with domain expertise in machine learning and deep learning, transformers, generative models, large language models, computer vision and multimodal models. You will devise innovative solutions at scale, pushing the technological and science boundaries. You will guide the design, modeling, and architectural choices of state-of-the-art large language models and multimodal models. You will devise and implement new algorithms and new learning strategies and paradigms. You will be technically hands-on and drive the execution from ideation to productionization. You will work in collaborative environment with other technical and business leaders, to innovate on behalf of the customer.

Do you want to be part of a team that's revolutionizing Amazon's fulfillment and packaging technology? Can you commit to optimizing systems that process tens-of-millions of customer packages daily with the lowest cost to serve and a defect-free customer experience? Do you have a passion for solving complex science challenges and building a sustainable e-commerce experience? Your statistical and machine learning skills can help make that a reality on the Mechatronics and Sustainable Packaging team. We are seeking a Principal Applied Scientist who will join a team of experts in the field of Statistics, Operational Research, Machine Learning (ML), Computer Vision and Generative AI to work together to break new ground in the world of automated packaging solutions. You'll work in a collaborative environment where you can pursue ambitious research with many peta-bytes of data, work on problems that haven’t been solved before, quickly implement and deploy your algorithmic ideas at scale, understand whether they succeed via statistically relevant experiments across millions of customers, and publish your research. You'll see the work you do directly improve the packaging experience of Amazon customers in the fulfillment technology space. If you are interested in robotics, computer vision, machine learning, statistics, big data, and building scalable solutions, this role is for you. The successful candidate will have a PhD in Computer Science, Statistics, or Engineering with a strong focus on data analysis, machine learning, generative AI or a related field, and 10+ years of practical experience solving complex problems in computer vision, anomaly detection, robotics. or multi-modal classification systems. Manufacturing, packaging and/or logistic experience is a plus, but not a requirement Key job responsibilities - Advance exploratory research projects in machine learning, statistics and related fields to create defect-free packaging customer experiences - Analyze large amounts of Amazon shipments to discover patterns, find opportunities, and develop highly innovative, scalable algorithms to seize these opportunities - Validate new or improved models via statistically relevant experiments across millions of customers - Work closely with software engineering teams to build scalable prototypes for testing, and integrate successful models and algorithms in production systems at very large scale

The Learning & Development Science team in Amazon Logistics (AMZL) builds state-of-the-art Artificial Intelligence (AI) solutions for enhancing leadership and associate development within the organization. We develop technology and mechanisms to map the learner journeys, answer real-time questions through chat assistants, and drive the right interventions at the right time. As an Applied Scientist on the team, you will play a critical role in driving the design, research, and development of these science initiatives. The ideal candidate will lead the research on learning and development trends, and develop impactful learning journey roadmap that align with organizational goals and priorities. By parsing the information of different learning courses, they will utilize the latest advances in Gen AI technology to address the personalized questions in real-time from the leadership and associates through chat assistants. Post the learning interventions, the candidate will apply causal inference or A/B experimentation frameworks to assess the associated impact of these learning programs on associate performance. As a part of this role, this candidate will collaborate with a large team of experts in the field and move the state of learning experience research forward. They should have the ability to communicate the science insights effectively to both technical and non-technical audiences. Key job responsibilities * Apply science models to extract actionable information from learning feedback * Leverage GenAI/Large Language Model (LLM) technology for scaling and automating learning experience workflows * Design and implement metrics to evaluate the effectiveness of AI models * Present deep dives and analysis to both technical and non-technical stakeholders, ensuring clarity and understanding and influencing business partners * Perform statistical analysis and statistical tests including hypothesis testing and A/B testing * Recognize and adopt best practices in reporting and analysis: data integrity, test design, analysis, validation, and documentation

AWS Sales, Marketing, and Global Services (SMGS) is responsible for driving revenue, adoption, and growth from the largest and fastest growing small- and mid-market accounts to enterprise-level customers including public sector. The AWS Global Support team interacts with leading companies and believes that world-class support is critical to customer success. AWS Support also partners with a global list of customers that are building mission-critical applications on top of AWS services. The Generative Artificial Intelligence (AI) Innovation Center team at AWS provides opportunities to innovate in a fast-paced organization that contributes to game-changing projects and technologies leveraging cutting-edge generative AI algorithms. As an Applied Scientist, you'll partner with technology and business teams to build solutions that surprise and delight our customers. We’re looking for Applied Scientists capable of using generative AI and other ML techniques to design, evangelize, and implement state-of-the-art solutions for never-before-solved problems. Key job responsibilities - Collaborate with scientists and engineers to research, design and develop cutting-edge generative AI algorithms to address real-world challenges - Work across customer engagement to understand what adoption patterns for generative AI are working and rapidly share them across teams and leadership - 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 for generative AI - 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. A day in the life Here at AWS, we embrace our differences. We are committed to furthering our culture of inclusion. We have ten employee-led affinity groups, reaching 40,000 employees in over 190 chapters globally. We have innovative benefit offerings, and host annual and ongoing learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences. Amazon’s culture of inclusion is reinforced within our 16 Leadership Principles, which remind team members to seek diverse perspectives, learn and be curious, and earn trust. About the team Diverse Experiences AWS values diverse experiences. Even if you do not meet all of the qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying. Why AWS? Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that’s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses. Inclusive Team Culture Here at AWS, it’s in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences, inspire us to never stop embracing our uniqueness. Mentorship & Career Growth We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional. Work/Life Balance We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve in the cloud. What if I don’t meet all the requirements? That’s okay! We hire people who have a passion for learning and are curious. You will be supported in your career development here at AWS. You will have plenty of opportunities to build your technical, leadership, business and consulting skills. Your onboarding will set you up for success, including a combination of formal and informal training. You’ll also have a chance to gain AWS certifications and access mentorship programs. You will learn from and collaborate with some of the brightest technical minds in the industry today.