Careers

Are you excited about developing state of the art Machine Learning (ML) capabilities to power Amazon's robotic storage solutions? Are you looking for opportunities to build and deploy Machine Learning models on real problems at truly vast scale? At Amazon Robotics we are on a mission to build high-performance autonomous systems that perceive and act to further improve our world-class customer experience - at Amazon scale. The Robotic Storage Technologies (RST) team at Amazon Robotics is seeking a passionate, collaborative, hands-on Applied Scientist to develop algorithms that foster optimal choice selection in Amazon's next generation robotic storage systems. You will explore and leverage huge amounts of inventory and robotic transactional data from our growing network of warehouses across the globe. You will utilize a combination of machine learning, reinforcement learning, and optimization methods to drive high performance that scales and adapts under dynamic operating conditions. This work spans from early research and simulation of new ideas through deployment and continuous improvements as our solutions and Amazon's needs continually evolve. The ideal candidate for this position will be familiar with planning or learning algorithms at both the theoretical and implementation levels. You will have the chance to solve complex scientific problems and see your solutions come to life in Amazon’s warehouses! Key job responsibilities - Research new ideas and contribute to the vision of our science roadmap. - Design and develop models and algorithms that perform at Amazon scale. - Work closely with software engineering teams to deploy your innovations. - Monitor, troubleshoot, and continuously improve production in performance. - Contribute to development of simulation and other forms of offline policy evolution. - Publish your work at major conferences/journals. A day in the life On a typical day in this role you will work to progress your research projects; meet with robotic storage engineering, systems, and solutions stakeholders; brainstorm with other scientists on the team and participate in team processes. You will follow your research projects though the entire life cycle of design, prototype implementation, evaluation, analysis, and you will communicate your findings and results through technical papers and reports. You will collaborate with software development teams to implement your ideas in production software services and design experiments to pilot your algorithms and models in Amazon's robotic warehouses. Amazon offers a full range of benefits that support you and eligible family members, including domestic partners. Benefits can vary by location, the number of regularly scheduled hours you work, length of employment, and job status such as seasonal or temporary employment. The benefits that generally apply to regular, full-time employees include: 1. Medical, Dental, and Vision Coverage 2. Maternity and Parental Leave Options 3. Paid Time Off (PTO) 4. 401(k) Plan If you are not sure that every qualification on the list above describes you exactly, we'd still love to hear from you! At Amazon, we value people with unique backgrounds, experiences, and skillsets. If you’re passionate about this role and want to make an impact on a global scale, please apply! About the team Robotic Storage Technologies (RST) owns automation of storage and retrieval solutions in Amazon's vast network of fulfillment centers across the globe. Our solutions are driven by fleets of hundreds of robots, and our customers are operations engineers and associates who help fulfill millions of Amazon.com orders per day. You will be part of a team of scientists embedded within the software organization that supports the solutions you help to deploy.

The Central Science Team within Amazon’s People Experience and Technology org (PXTCS) uses economics, behavioral science, statistics, and machine learning to proactively identify mechanisms and process improvements which simultaneously improve Amazon and the lives, well-being, and the value of work to Amazonians. We are an interdisciplinary team, which combines the talents of science and engineering to develop and deliver solutions that measurably achieve this goal. We are looking for a Principal Economist who is able to provide structure around complex business problems, hone those complex problems into specific, scientific questions, and test those questions to generate insights. The ideal candidate will work with various science, engineering, operations, and analytics teams to estimate models and algorithms on large scale data, design pilots and measure their impact, and transform successful prototypes into improved policies and programs at scale. They will lead research projects to produce robust, objective research results and insights which can be communicated to a broad audience inside and outside of Amazon. Ideal candidates will work closely with business partners to develop science that solves the most important business challenges. They will work well in a team setting with individuals from diverse disciplines and backgrounds. They will serve as an ambassador for science and a scientific resource for business teams, so that scientific processes permeate throughout the HR organization to the benefit of Amazonians and Amazon. Ideal candidates will own the development of scientific models and manage the data analysis, modeling, and experimentation that is necessary for estimating and validating models. They will be customer-centric – clearly communicating scientific approaches and findings to business leaders, listening to and incorporate their feedback, and delivering successful scientific solutions. About the team The Central Science Team within Amazon’s People Experience and Technology org (PXTCS) uses economics, behavioral science, statistics, and machine learning to proactively identify mechanisms and process improvements which simultaneously improve Amazon and the lives, well-being, and the value of work to Amazonians. We are an interdisciplinary team, which combines the talents of science and engineering to develop and deliver solutions that measurably achieve this goal.

Have you ever wondered how Amazon predicts when your order will arrive and how we ensure that it actually arrives on at the promised date/time? Have you wondered where all those Amazon semi-trucks on the road are headed? Are you passionate about increasing efficiency and reducing carbon footprint? Does the idea of having worldwide impact on Amazon's logistics network including our planes, trucks, and vans sound exciting to you? If so, then we want to talk with you! At Amazon's Supply Chain Optimization Technologies (SCOT), we are tasked with optimizing the fulfillment on customer orders so that we fulfill all orders worldwide in the most intelligent manner while ensuring Amazon customers get their orders on time. SCOT- Fulfillment Optimization (FO) owns and operates OR/ML and simulation systems that continually optimize the distribution of tens of millions of products across Amazon’s warehouses in the most cost-effective manner, utilizing large scale optimization techniques and distributed computing in trying to reduce overall transportation costs while improving the customer experience. We are focused on saving hundreds of millions of dollars using Optimization, machine learning, and scalable distributed software on the cloud that automates and optimizes inventory and shipments to customers under the uncertainty of demand, pricing and supply. We’re looking for a passionate, results-oriented, and inventive scientist who can create and improve models for our outbound transportation planning systems. In addition, you will be working on design, development and evaluation of highly innovative models for solving complex business problems in the area of outbound transportation planning and execution systems. You will work closely with our product managers and software engineers to disambiguate complex supply chain problems and create optimization solutions to solve those problems at scale. You will directly impact our direct customers, and even play with big data and incredible scale in the background.

Are you excited by the idea of developing algorithms to improve the shopping experience for Amazon customers? Are you looking for new challenges and to solve hard science problems while applying state-of-the-art modeling techniques? Join us and you'll help make the shopping experience better for millions of customers while also advancing the state of Amazon's science through publishing research! Key job responsibilities - Develop and apply new machine learning algorithms - Use expertise in supervised learning and causal inference to improve ML performance - Scale optimization techniques to drive business value - Design A/B tests and conduct statistical analysis on their results - Work with distributed machine learning and statistical algorithms to harness enormous volumes of data at scale to serve our customers - Present and publish science research, contributing to Amazon's science community - Mentor junior engineers and scientists. - Work closely with internal stakeholders like the business teams, engineering teams and partner teams and align them with respect to your focus area About the team Our team's mission is to surface the right payments-related recommendations to customers at the right time, helping create a rewarding and successful shopping experience for Amazon's customers. Our team's culture is highly collaborative, with an emphasis on supporting each other and learning from one another. We dedicate time each week to focus on personal development and expanding our knowledge as a team. We also highly value having a big impact, both for Amazon's business and for our customers.

External job description As a Sr. Applied Scientist, you will be responsible for assessing and optimizing the performance and reliability of our new and emerging category of devices – Kuiper Customer Terminal. Project Kuiper is an initiative to launch a constellation of Low Earth Orbit satellites that will provide low-latency, high-speed broadband connectivity to un-served and under-served communities around the world. In this role, you will use expertise in physical sciences, theoretical, numerical or empirical techniques to create scalable models representing response of physical systems or devices, including: - Applying domain scientific expertise towards developing innovative analysis and tests to study viability of new materials, designs or processes - Working closely with engineering teams to drive validation, optimization and implementation of hardware design or software algorithmic solutions to improve product and customer risks - Establishing scalable, efficient, automated processes to handle large scale design and data analysis - Conducting research into use conditions, materials and analysis techniques - Tracking general business activity including device health in field and providing clear, compelling reports to management on a regular basis - Developing, implementing guidelines to continually optimize design processes - Using simulation tools like LS-DYNA, and Abaqus for analysis and optimization of product design - Using of programming languages like Python and Matlab for analytical/statistical analyses and automation - Demonstrating strong understanding across multiple physical science domains, e.g. structural, thermal, fluid dynamics, and materials - Developing, analyzing and testing structural solutions from concept design, feature development, product architecture, through system validation - Supporting product development and optimization through application of analysis and testing of complex electronic assemblies using advanced simulation and experimentation tools and techniques

Are you excited about solving complex business problems at scale through GenAI? Are you fascinated about the application of Agentic AI and LLMs on real-life scenarios? Are you looking to invent solutions that drive Autonomous Artificial Intelligence? If so, we are looking for you to fill a challenging position on Amazon's Trustworthy Shopping Experience (TSE) team. At TSE, our vision is to guarantee customers a worry-free shopping experience by earning their trust that the products they buy are safe, authentic, and compliant with regulations and policy, and giving them the confidence that Amazon stands behind every product and will make it right in the rare chance anything goes wrong. We do this in close partnership with our selling partners and empower them with best-in-class tools and expertise required to offer a high-quality selection of compliant products that customers trust. When we do this consistently, we help selling partners grow their business and power their long-term success. As a Senior Applied Scientist on the team, you will be responsible for delivering the science solutions required to automate complex manual investigation processes, especially by leveraging LLMs. You will handle Amazon scale use-cases with significant impact to the cost of serving Customers. Key job responsibilities - You invent and design new solutions for scientifically-complex problem areas and/or opportunities in existing or new business initiatives. - You design experiments and define the science approach to solve critical business use-cases for automating manual work that involves unstructured text, documents, images, symbols, etc. - Your work focuses on ambiguous problem areas at the product level, where the business problem or opportunity may not yet be crisply defined. - You drive or heavily influence the design of scientifically-complex software solutions or systems, for which you personally write significant parts of the critical scientific novelty. - You provide a system-wide view and design guidance for solutions that can be brand new or evolve from existing ones. - You apply and set the example for best practices in software engineering, and systematically peer review code written by your team members. - You set standards and proactively drive components to use and improve on state-of-the-art techniques. - You autonomously drive thoughtful discussions with customers, engineers, and scientist peers, and build consensus on larger projects and factor complex efforts into independent tasks that can be performed by you and others. About the team Investigation technology Product team in TSE is responsible for the human-in-the-loop products and technology used in the risk investigations at Amazon. The team is also responsible for reducing the cost of performing the investigations, by automating wherever possible and optimizing the experience where manual interventions are needed. The team leverages state-of-the art technology and GenAI to deliver the products and associated goals.

The Artificial General Intelligence (AGI) team is looking for a highly skilled and experienced Senior Applied Scientist, to lead the development and implementation of cutting-edge algorithms and models for supervised fine-tuning, reinforcement learning through human feedback and complex reasoning; with a focus across text, image, and video modalities. As a Senior Applied Scientist, you will play a critical role in driving the development of Generative AI (GenAI) technologies that can handle Amazon-scale use cases and have a significant impact on our customers' experiences. Key job responsibilities - Collaborate with cross-functional teams of engineers, product managers, and scientists to identify and solve complex problems in GenAI - Design and execute experiments to evaluate the performance of different algorithms and models, and iterate quickly to improve results - Think big about the arc of development of GenAI over a multi-year horizon, and identify new opportunities to apply these technologies to solve real-world problems - Communicate results and insights to both technical and non-technical audiences, including through presentations and written reports - Mentor and guide junior scientists and engineers, and contribute to the overall growth and development of the team

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. Key job responsibilities - Work backwards from customer problems to research and develop novel machine learning solutions for music and podcast recommendations. Through A/B testing and online experiments done hand-in-hand with engineering teams, you'll implement and validate your ideas and solutions. - Advocate solutions and communicate results, insights and recommendations to stakeholders and partners. - Produce innovative research on recommender systems that shapes the field and meets the high standards of peer-reviewed publications. You'll cement your team's reputation as thought leaders pioneering new recommenders. Stay current with advancements in the field, adapting latest in literature to build efficient and scalable models A day in the life Lead innovation in ML to shape Amazon Music experiences for millions. Collaborate with talented engineers and scientists to guide research and build scalable models across our audio portfolio - music, podcasts, live streaming, and more. Drive experiments and rapid prototyping, leveraging Amazon's data at scale. Innovate daily alongside world-class teams to delight customers worldwide through personalization. About the team The team is responsible for models that underly all of Amazon Music’s recommendations across content types on mobile, web and Alexa. You will collaborate with a team of product managers, applied scientists and software engineers delivering meaningful recommendations, personalized for each of the millions of customers using Amazon Music globally. As a scientist on the team, you will be involved in every aspect of the development lifecycle, from idea generation and scientific research to development and deployment of advanced models. You will work closely with engineering to realize your scientific vision.

Are you looking for an opportunity to build an LLM-based enterprise-grade, highly available, large scale solution? Does it excite you to find patterns and build generic, composable solutions to solve complex problems? Are you looking for inventing newer and simpler ways of building solutions? If so, we are looking for you to fill a challenging position in Alexa Enterprise (AE) team. AE brings the power of Alexa voice assistant to enterprise partners in industries such as hospitality and senior living. We tackle pressing challenges like workforce shortage. We are inventing Large Language Models (LLM)-driven interactions to create memorable moments for users while simultaneously boosting partner revenues and reinforcing brand identity. Beyond managed properties, AE extends Alexa's reach to premium third-party devices, seamlessly integrating with household names like Samsung, LG, and Sonos, thus amplifying its impact across diverse ecosystems. AE team is looking for a passionate, highly skilled and inventive Senior Applied Scientist, with a strong machine learning background, to lead the development and implementation of state-of-the-art ML systems for Alexa Enterprise use cases. As a Senior Applied Scientist in the team, you will play a critical role in driving the development of conversational assistants, in particular those based on Large Language Models (LLM's), that meet enterprise standards. You will handle Amazon-scale use cases with significant impact on our customers' experiences. Key job responsibilities - You will analyze, understand and improve user experiences by leveraging Amazon’s heterogeneous data sources and large-scale computing resources to accelerate advances in artificial intelligence - You will work on core LLM technologies, including developing best-in-class modeling, prompt optimization algorithms to enable Conversation AI use cases - Build and measure novel online & offline metrics for personal digital assistants and customer scenarios, on diverse devices and endpoints - Create, innovate, and deliver deep learning, policy-based learning, and/or machine learning-based algorithms to deliver customer-impacting results - Perform model/data analysis and monitor metrics through online A/B testing

Do you want a role with deep meaning and the ability to make a massive impact? Hiring top talent is not only critical to Amazon’s success—it can literally change the world. It took a lot of great hires to deliver innovations like AWS, Prime, and Alexa, which make life better for millions of customers around the world every day. As part of the Intelligent Talent Acquisition (ITA) team, you'll have the opportunity to reinvent the hiring process and deliver unprecedented scale, sophistication, and accuracy that Amazon's Talent Acquisition operations need. ITA is an industry-leading people science and technology organization made up of scientists, engineers, analysts, product professionals and more. Our shared goal is to fairly and precisely connect the right people to the right jobs. Last year, we delivered over 6 million online candidate assessments, replacing the "game of chance" with a merit-based approach that gives candidates the chance to showcase their true skills. Each year we help Amazon deliver billions of packages around the world by making it possible to hire hundreds of thousands of associates in the right quantity, at the right location and at exactly the right time. You’ll work on state-of-the-art research, advanced software tools, new AI systems, and machine learning algorithms to solve complex hiring challenges. Leveraging Amazon's in-house tech stack built on AWS, you'll have the autonomy and flexibility to bring innovative solutions to life. One day, we can bring these solutions to the rest of the world. Join ITA in using technologies to transform the hiring landscape and make a meaningful difference in people's lives. Together, we can solve the world's toughest hiring problems. Within ITA, the Candidate Generation team uses scientific experimentation, causal inference, generative AI, machine learning, and forecasting techniques to bring new and returning candidates to the top of the recruitment funnel. Driven by the goal of ensuring every marketing dollar is spent efficiently and effectively, the Candidate Generation team builds innovative decisioning products that provide tailored recommendations for recruiting challenges across a wide array of marketing channels globally. Our award-winning solutions tackle complex and ambiguous problems by applying science methodically and creatively, increasing candidate engagement while driving down costs. As a member of Candidate Generation, your work will modernize the field of Marketing and revolutionize the way we find and attract Amazonian talent.