Careers

Here at Amazon, we embrace our differences. We are committed to furthering our culture of diversity and inclusion of our teams within the organization. How do you get items to customers quickly, cost-effectively, and—most importantly—safely, in less than an hour? And how do you do it in a way that can scale? Our teams of hundreds of scientists, engineers, aerospace professionals, and futurists have been working hard to do just that! We are delivering to customers, and are excited for what’s to come. Check out more information about Prime Air on the About Amazon blog (https://www.aboutamazon.com/news/transportation/amazon-prime-air-delivery-drone-reveal-photos). If you are seeking an iterative environment where you can drive innovation, apply state-of-the-art technologies to solve real world delivery challenges, and provide benefits to customers, Prime Air is the place for you. Come work on the Amazon Prime Air Team! We are seeking a highly skilled Navigation Scientist to help develop advanced algorithms and software for our Prime Air delivery drone program. In this role, you will conduct comprehensive navigation analysis to support cross-functional decision-making, define system architecture and requirements, contribute to the development of flight algorithms, and actively identify innovative technological opportunities that will drive significant enhancements to meet our customers' evolving demands. Export Control License: This position may require a deemed export control license for compliance with applicable laws and regulations. Placement is contingent on Amazon’s ability to apply for and obtain an export control license on your behalf.

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 Bedrock AI Data Team in Amazon Web Services (AWS) is looking for a Language Data Scientist to collaborate in developing solutions for natural language data collections. This position is an opportunity to apply your expertise in a challenging but supportive environment. The mission of the Bedrock AI Data Team is to engineer the datasets critical to the success of AWS’s Bedrock services. From human evaluations to Responsible AI safeguards to Retrieval-Augmented Generation and beyond, these products make Generative AI enterprise-ready and safe for users, impacting millions of people every day. We are a group of language engineers, linguists, data scientists, data engineers, and program managers, and we partner closely with the science, engineering, and product teams. We are customer obsessed and committed to delivering results with the highest quality and integrity. As a Language Data Scientist, you will start by diving deep into a couple of critical projects for Bedrock services to drive these projects forward. You will collaborate with fellow language data scientists, program managers, as well as stakeholders in science, engineering, and product teams to understand the role data plays in developing models that meet customer needs. You will analyze, follow, and improve processes for collecting and annotating LLM inputs and outputs, assessing data quality, and automating where appropriate. You will then expand your scope by using the principles of data-centric AI to understand the role our data plays with regard to model performance specifically, as well as the larger ML pipeline. You will apply state-of-the-art Generative AI techniques to analyze how well our data represents human language and run experiments to gauge downstream interactions. You will work collaboratively with other language data scientists and scientists to design and implement principled strategies for data optimization. Key job responsibilities - Source, validate, and deliver high-quality language artifacts and linguistic data - Collaborate with stakeholders to design data collection and development efforts - Oversee the progress and quality of several data collection and annotation projects at a time - Advocate for strict adherence to data collection guidelines and quality thresholds - Extend existing data collection, annotation, and quality assurance efforts to support feature and language expansion - Innovate on data collection methodologies, guidelines, quality metrics to support new requests - Automate repetitive workflows and improve existing processes About the team The Bedrock AI Data Team at AWS is responsible for delivering high-quality annotated data and a variety of language artifacts to ensure the best performance of different AWS LLM services. These Generative AI services enable customers to readily add intelligence to their business operations and AI applications to drive positive outcomes. 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. 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. 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.

Amazon is looking for talented Postdoctoral Scientists to join our Corporate Projects team for a one-year, full-time research position. Corporate Projects is a team that sits within the broader Corporate Development organization at Amazon. We seek to bring net-new, strategic projects to life by working together with customers and evolving projects from ZERO-to-ONE. To do so, we deploy our resources towards proofs-of-concept and pilot programs and develop them from high-level ideas (the ZERO) to tangible short-term results that provide validating signal and a path to scale (the ONE). We work with our customers to develop and create net-new opportunities by relentlessly scouring all of Amazon and finding new and innovative ways to strengthen and/or accelerate the Amazon Flywheel. As a Postdoctoral Scientist on the Corporate Projects team, you will develop algorithms and approaches to identifying and characterizing people and objects in an FC scene. The postdoc will work across Amazon to learn about programs developing related systems take the data collected by the Toucan team in the field to create and train a vision classifier. The postdoc will collaborate with other team members to test it and refine it 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.

At Global Mile Expansion team, our vision is to become the carrier of choice for all of our Selling Partners cross-border shipping needs, offering complete set of end to end cross border solutions from key manufacturing hubs to footprint countries supporting business who use Amazon to grow their business globally. As we expand, the need for comprehensive business insight and robust demand forecasting to aid decision making on asset utilization especially where we know demand will be variable becomes vital, as well as operational excellence. We are building business models involving large amounts of data and Macro economic inputs to produce the robust forecast to help the operational excellence and continue improving the customer experience. We are looking for an experienced economist who can apply innovative modelling techniques to real-world problems, and convert it to highly business-impacting solutions. Key job responsibilities - Experienced in using mathematical and statistical approach to create new, scalable solutions for business problems - Analyze and extract relevant information from business data to help automate and optimize key processes - Design, develop and evaluate highly innovative models for predictive learning - Establish scalable, efficient, automated processes for large scale data analyses, model development, model validation and model implementation - Research and implement statistical approaches to understand the business long-term and short-term trend and support the strategies

Amazon is looking for world class Applied Scientist to join its AWS AI Labs with expertise in AI-assistants focusing on conversational- retrieval augmented generation (RAG), agent orchestration, multi-modal and multi-lingual chat agents, etc. You will be joining a team of applied scientists developing robust and scalable machine learning solutions for enterprise conversational assistants. You will interact in a cross-functional capacity with product and engineering leaders, as well as with our customers and with the academic community. You will be at the heart of a growing and exciting focus area for AWS and work with acclaimed engineers and world-class scientists. About the team Amazon Q Business is a generative AI–powered assistant that can answer questions, provide summaries, generate content, and take actions, securely completing the tasks based on data and information in your enterprise systems. It empowers employees to be more creative, data-driven, efficient, prepared, and productive. As member of Q team, you’ll work on optimizing large language models in an efficient manner and implementing solutions to enhance and build new functionalities into Q assistant. 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. 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. Hybrid Work We value innovation and recognize this sometimes requires uninterrupted time to focus on a build. We also value in-person collaboration and time spent face-to-face. Our team affords employees options to work in the office every day or in a flexible, hybrid work model near one of our U.S. Amazon offices.

Amazon Search JP builds features powering product search on the Amazon JP shopping site and expands the innovations to world wide. As an Applied Scientist on this growing team, you will take on a key role in improving the NLP and ranking capabilities of the Amazon product search service. Our ultimate goal is to help customers find the products they are searching for, and discover new products they would be interested in. We do so by developing NLP components that cover a wide range of languages and systems. As an Applied Scientist for Search JP, you will design, implement and deliver search features on Amazon site, helping millions of customers every day to find quickly what they are looking for. You will propose innovation in NLP and IR 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 search engine 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 - Designing and implementing new features and machine learned models, including the application of state-of-art deep learning to solve search matching, ranking and Search suggestion problems. - Analyzing data and metrics relevant to the search experiences. - 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 We are open to hiring candidates to work out of one of the following locations: Beijing, 11, CHN | Shanghai, 31, CHN

The Amazon Devices team designs and engineers high-profile consumer electronics, including the best-selling Kindle family of products. We have also produced groundbreaking devices like Fire tablets, Fire TV, Amazon Dash, and Amazon Echo. What will you help us create? The Team: How often have you had an opportunity to be a founding member of a team that is solving a significant problem through innovative technology? Would you like to know more about how we are envisioning the use of machine learning and GenAI to solve these problems? If this sounds intriguing, then we’d like to talk to you about a role on our team that's tackling a set of problems requiring significant innovation and scaling. As a Sr. Applied Scientist, you will design, evangelize, and implement state-of-the-art solutions for never-before-solved problems, helping Amazon Device to provide customer great products. This role will be a key member of a Science and Data technology team based in Guadalajara, Mexico. You will work closely with other scientists, machine learning experts, engineers to design and run experiments, research new algorithms, and find new ways to improve Amazon Device Services & Software products. You will partner with technology and product leaders to solve business and technology problems using scientific approaches to build new services that surprise and delight our customers. Our scientists work closely with software engineers to put algorithms into practice. They also work on cross-disciplinary efforts with other scientists within Amazon. The key responsibility for this role include: - Define proper output business Metrics, and build input models to identify patterns and drivers of the output. Drive actions at scale using scientifically-based methods and decision making. - Design and develop complex mathematical, statistical, Machine Learning, GenAI models and apply them to define strategic and tactical needs and drive the appropriate business and technical solutions - Design experiments, test hypotheses, and build actionable models - Prototype these models by using modeling languages such as R or in software languages such as Python. - Work with software engineering teams to drive scalable, real-time implementations - Utilizing Amazon systems and tools to effectively work with terabytes of data

Amazon’s Automated Inventory Management (AIM) team is looking for passionate, hard-working, and talented individuals to join our fast paced, stimulating environment to help invent the future of business ownership with Technology, and to translate big data into actionable insights. The AIM team is part of the Supply Chain Optimization Technology (SCOT) Team within the Operations Organization. As an Applied Scientist on the AIM team, you will design quantitative systems, forecasting models and solve real world problems using the latest machine learning techniques. You will also work with a team of Product Managers, Business Intelligence Engineers and Software Engineers to research and build solutions to provide insights to business leaders at the most senior levels throughout the company. Key job responsibilities Implement statistical and machine learning methods to solve complex business problems Research new ways to improve predictive and explanatory models Directly contribute to the design and development of automated prediction systems and ML infrastructure Build models that can detect supply chain defects and explain variance to the optimal state Collaborate with other researchers, software developers, and business leaders to define the scientific roadmap for this team

Amazon's Optimal Inventory Health (OIH) org in Supply Chain Optimization (SCOT) group is looking for a Principal Applied Scientist to optimize one of the most complex eCommerce systems in the world. The Optimal Inventory Health (OIH) drives long-term cash flow (LTFCF) growth by determining optimal inventory dispositions under uncertainties in demand, pricing, and supply across Amazon’s 21 marketplaces global network. OIH is in the unique position within SCOT to drive the joint optimization across supply chain and marketing across the levers of Markdowns, Removals, Outlet, Deals, Sponsored Ads, and Paid Search etc. Our systems delivers hundreds of million dollar saving to Amazon each year. The Principal Applied Scientist will lead the science vision and implementation to optimize across inventory disposition channels and deliver best experience to Amazon customers through those levers. We are investing and building the next generation inventory disposition decision models based on cutting-edge technologies like Reinforcement learning, Causal inference, Deep Learning Prediction etc. Academic and/or practical background in Machine Learning and Operations Research are particularly relevant for this position. Experience in model-based engineering and/or multidisciplinary analysis & optimization is also a plus. This position requires drive and self-motivation, superior analytical thinking, data-driven disposition, application of technical knowledge to a business context, effective collaboration with fellow scientists, software development engineers, and product managers, effective communication of technical designs to technical and non-technical audiences, and close partnership with many stakeholders from operations, finance, IT, and business leadership. Key job responsibilities - Seek to understand in depth the end to end value chain of eCommerce across supply chain and marketing and identify areas of opportunities to grow our business using science solutions. - Lead science strategy and roadmap in OIH space - Drive alignment across organizations to achieve business goals - Lead/guide scientists and engineers across teams to develop, test, launch and improve of science models designed to optimize inventory value and customer experience. - Be responsible for communicating our innovations to the broader internal & external scientific community and business leadership. - Mentor and guide the applied scientists in our organization and hold us to a high standard of technical rigor and excellence in ML. A day in the life - You will engage with distinguished scientists and Senior Principal scientists across organizations to shape the vision of the eCommerce decision systems across supply chain and marketing. - You will collaborate with talented product managers and software engineers to build the end to end systems. - You will work with stakeholders across retail, supply chain, finance etc. to understand the business operation process and bottlenecks and build solution to provide the best experience to Amazon customers through automated OIH actions. - You have the access to the richest eCommerce data and will be able to see the actual significant business impact quickly with the models you build. About the team Supply Chain Optimization Technology (SCOT) is the core of the Amazon eCommerce business, which leverage science models and systems to automate the decisions and operations of the most complex supply chain in the world. Optimal Inventory Health (OIH) maximize the inventory value in Amazon through all the levers across traffic, marketing, pricing and reverse logistics.

Are you interested in changing the Digital Reading Experience? We are from Kindle Books Team looking for a set of Scientists to take the reading experience in Kindle to next level with a set of innovations! We envision Kindle as the place where readers find the best manifestation of all written content optimized with features that enable them to get the most out of reading, and creators are able to realize their vision to customers quickly and at scale. Every time customers open their content, regardless of surface, they start or restart their reading in a familiar, useful and engaging place. We achieve this by building a strong foundation of core experiences and act as a force multiplier and partner for content creators (directly or indirectly) to easily innovate on top of Kindle's purpose built content experience stack in a simple and extensible way. We will achieve this by providing a best-in-class reading experience, unique content experiences, and remaining agile in meeting the evolving needs and preferences of our users. Our goal is to foster long-lasting reading habits and make us the preferred destination for enriching literary experiences. We are building a In The Book Science team and looking for Scientists, who are passionate about Reading and are willing to take Reading to the next level. Every Book is a complex structure with different entities, layout, format and semantics, with more than 17MM eBooks in our catalog. We are looking for experts in all domains like core NLP, Generative AI, CV and Deep Learning Techniques for unlocking capabilities like analysis, enhancement, curation, moderation, translation, transformation and generation in Books based on Content structure, features, Intent & Synthesis. Scientists will focus on Inside the book content and semantically learn the different entities to enhance the Reading experience overall (Kindle & beyond). They have an opportunity to influence in 2 major phases of life-cycle - Publishing (Creation of Books process) and Reading experience (building engaging features & representation in the book thereby driving reading engagement). Key job responsibilities - 5+ years of building machine learning models for business application experience - PhD, or Master's degree and 6+ years of applied research experience - Knowledge of programming languages such as C/C++, Python, Java or Perl - Experience programming in Java, C++, Python or related language - You have expertise in one of the applied science disciplines, such as machine learning, natural language processing, computer vision, Deep learning - You are able to use reasonable assumptions, data, and customer requirements to solve problems. - You initiate the design, development, execution, and implementation of smaller components with input and guidance from team members. - You work with SDEs to deliver solutions into production to benefit customers or an area of the business. - You assume responsibility for the code in your components. You write secure, stable, testable, maintainable code with minimal defects. - You understand basic data structures, algorithms, model evaluation techniques, performance, and optimality tradeoffs. - You follow engineering and scientific method best practices. You get your designs, models, and code reviewed. You test your code and models thoroughly - You participate in team design, scoping and prioritization discussions. You are able to map a business goal to a scientific problem and map business metrics to technical metrics. - You invent, refine and develop your solutions to ensure they are meeting customer needs and team goals. You keep current with research trends in your area of expertise and scrutinize your results. - Experience in mentoring junior scientists A day in the life You will be working with a group of talented scientists on researching algorithm and running experiments to test solutions to improve our experience. This will involve collaboration with partner teams including engineering, PMs, data annotators, and other scientists to discuss data quality, model development and productionizing the same. You will mentor other scientists, review and guide their work, help develop roadmaps for the team.