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External job description Machine learning (ML) has been strategic to Amazon from the early years. We are pioneers in areas such as recommendation engines, product search, eCommerce fraud detection, and large-scale optimization of fulfillment center operations. The Generative AI team helps AWS customers accelerate the use of Generative AI to solve business and operational challenges and promote innovation in their organization. As an applied scientist, you are proficient in designing and developing advanced ML models to solve diverse challenges and opportunities. You will be working with terabytes of text, images, and other types of data to solve real-world problems. You'll design and run experiments, research new algorithms, and find new ways of optimizing risk, profitability, and customer experience. We’re looking for talented scientists capable of applying ML algorithms and cutting-edge deep learning (DL) and reinforcement learning approaches to areas such as drug discovery, customer segmentation, fraud prevention, capacity planning, predictive maintenance, pricing optimization, call center analytics, player pose estimation, event detection, and virtual assistant among others. 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. Key job responsibilities The primary responsibilities of this role are to: - Design, develop, and evaluate innovative ML models to solve diverse challenges and opportunities across industries - Interact with customer directly to understand their business problems, and help them with defining and implementing scalable Generative AI solutions to solve them - Work closely with account teams, research scientist teams, and product engineering teams to drive model implementations and new solution About the team ABOUT AWS: Diverse Experiences Amazon 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. 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. 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 and 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.

Are you a data enthusiast? Are you a creative big thinker who is passionate about using data and optimization tools to direct decision making and solve complex and large-scale challenges? If so, then this position is for you! We are looking for a motivated individual with strong analytic and communication skills to join the effort in evolving the fulfillment center network of tomorrow. At Amazon Worldwide Fulfillment Design and Engineering, we are designing the future and if you are in quest of an iterative fast-paced environment, where you can drive innovation through data visualization products, advance analytics and machine learning at scale, this is your opportunity. In this role, your main focus will be to perform analysis, synthesize information, identify business opportunities, provide project direction, and communicate design and technical requirements within the team and across stakeholder groups. You will learn current processes, build metrics, educate diverse stakeholder groups, assist science groups in initial solution design, and audit new flow implementations. A successful candidate in this position will have a background in communicating across significant differences, prioritizing competing requests, and quantifying decisions made. Key job responsibilities • Analyze, model and interpret data for Amazon warehouse operational performance • Data analysis, modeling, network flow prediction using Excel, Pivot tables, VBA, Tableau, SQL (Amazon Redshift), R, Python • Predictive analysis using Machine Learning models at scale • Create effective data analysis reports and communicate with stakeholders • Innovate and simplify data analysis process to standardize and enable automation • Support Worldwide Engineering teams by providing necessary data for of process flows and selection of various MHE's • Manage multiple data analysis projects and tasks simultaneously and effectively influence, negotiate, and communicate with internal and external business partners, contractors and vendors. • Support process improvement initiatives among site operations, engineering, and corporate systems groups by providing relevant data. • Develop data and optimization-based solutions to the best-in-class process flow to improve the throughput of the fulfillment facilities.

We are seeking a motivated and talented Applied Scientist to join our team at Amazon AGI (Artificial General Intelligence), advancing the state of the art in AGI models and directly impacting the experience and engagement of customers interacting with Amazon’s products and services. Our team works on diverse projects spanning Large Language Models, Information Retrieval, Natural Language Understanding, and Engagement optimization. Key job responsibilities In this role you will: - Leverage Large Language Models (LLMs) and transformer-based models for improving Amazon’s end-user experience and launching new features. - Perform hands-on data analysis and modeling with large data sets to develop insights that increase device usage and customer experience - Apply machine learning and natural language understanding techniques to improve our conversational interfaces and search algorithms - Run A/B experiments, evaluate the impact of your optimizations and communicate your results to various business stakeholders - Work closely with product managers and software engineers to design experiments and implement end-to-end solutions - Be a member of the Amazon-wide machine learning community, participating in internal and external Hackathons and Conferences - Help attract and recruit technical talent

An Applied Scientist in the Amazon Q for Business team is a significant and autonomous contributor who can push the envelope in a broad variety of areas related to deep learning, Retrieval Augmented Generation, natural language processing (NLP) research, and multimodal search and questin answsering. The Applied Scientist can transfer state-of-the-art research to solve real-world challenges on our customers’ behalf. The Applied Scientist II should have substantial hands-on experience with deep neural network based machine learning (ML) strong NLP or multimodal problem solving skill. The Applied Scientist should closely follow the latest advances in the academic field, while staying current with the development of LLM and deep learning multimodal models across the company. The Science team is responsible for the design, implementation and improvement of all the technologies at the foundation of Amazon Q for Business, including 1/ search and retrieval of textual, semistructured data (rich documents), structured data, and multimodal data; 2/ extractive and abstractive question answering over text, structure data and multi-modal sources; 3/ conversational AI, including interaction modes beyond simple text; 4/ Orchestration across a large number of applications connected to a LLM via plugins or agents, including planning to fulfill the user needs by combining multiple steps possibly across different applications; 5/ Reasoning, to extract complex insights from the appropriate data. Key job responsibilities An Applied Scientist should be able to independently execute complex research plans, and deliver high-quality results in the form of faithfully implemented models, well-designed and properly executed experiments, insightful analysis of data, and concise and accurate communication of conclusions. The Applied Scientist should have excellent teamwork skills, as the complexity and breadth of the Amazon Q for Business requires frequent interactions with other Scientists working in different work streams, as well as with Scientists from other projects with whom we collaborate on areas of common interest. Additionally, the Applied Scientist will regularly participate in meetings and discussions with Engineering and Product partners, and needs excellent communication skills to collaborate with colleagues with different backgrounds and skill sets. The Applied Scientist will engage in long-term projects, and, at the same time, customer obsession and bias for action will require diving deep in customer issues, provide suggestions to Engineering for short term mitigation, and formulate principled solutions for longer term investigation.. Applied Scientists are expected to actively engage the Science community within and beyond Amazon. They should actively publish their work, either as patents or as scientific papers at top-tier conferences. They should also help mentor junior and peer scientists or interns, within and across teams in Amazon. About the team 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.

Join us at the cutting edge of Amazon's sustainability initiatives to work on environmental and social advancements to support Amazon's long term worldwide sustainability strategy. At Amazon, we're working to be the most customer-centric company on earth. To get there, we need exceptionally talented, bright, and driven people. The Worldwide Sustainability (WWS) organization capitalizes on Amazon's scale & speed to build a more resilient and sustainable company. We manage our social and environmental impacts globally, driving solutions that enable our customers, businesses, and the world around us to become more sustainable. Sustainability Science and Innovation (SSI) is a multi-disciplinary team within the WW Sustainability organization that combines science, economics, statistics, machine learning, product development, analytics, and engineering expertise. We use this expertise to identify, develop and evaluate the science and innovations necessary for Amazon, customers, and partners to meet their long-term sustainability goals and commitments. We are seeking an experienced Research Scientist to play a key role in our work to achieve our long-term sustainability and climate commitments. In this role, you will lead the development of economic, statistical, and machine learning/AI-based models that will drive critical decarbonization investment decisions for Amazon Sustainability. You will leverage complex data from diverse internal and external sources, developing state-of-the-art models informed by techno-economics, physical and engineering-based models, or economic theory. The successful applicant will lead by example, pioneering science-vetted, data-driven approaches, and working collaboratively to implement strategies that align with Amazon's long-term sustainability vision. You will be at the forefront of exploring and resolving complex sustainability issues, bringing innovative ideas to the table, and making meaningful contributions to projects across SSI's portfolio. This role not only demands technical expertise but also a strategic mindset and the agility to adapt to evolving sustainability challenges through self-driven learning and exploration. In this position, you will deeply partner with peer scientists, sustainability specialists, economists, data engineers, product managers, and engineers. Your work will be crucial in evaluating the cost and efficacy of different strategies for reducing carbon emissions and achieving sustainability outcomes. You'll also build mechanisms to help key stakeholders understand, inspect, and apply your results, as well as make iterative improvements. Key job responsibilities - Develop and implement advanced theoretical, statistical, and empirical prediction models to make projections over various time horizons, incorporating techno-economic, physical, engineering-based, and economic theory principles. - Conduct comprehensive analyses to evaluate the cost-effectiveness and impact of various carbon emission reduction strategies and sustainability initiatives. - Design and implement robust mechanisms to facilitate stakeholder understanding, inspection, and application of research results, enabling continuous improvement. - Develop key performance metrics, benchmarks, and A/B testing methodologies to enhance the transparency and effectiveness of carbon abatement options. - Communicate complex findings and recommendations to senior business leaders and the broader scientific community, influencing cross-functional stakeholders through clear, high-quality technical deliverables. - Lead early-stage strategic sustainability initiatives, driving stakeholder engagement to scale high-value projects across the organization. - Leverage complex data from diverse internal and external sources to drive critical decarbonization investment decisions for Amazon Sustainability. About the team Diverse Experiences: World Wide Sustainability (WWS) 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: 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 flexible work hours and arrangements are part of our culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve.

About Amazon Health Amazon Health’s mission is to make it dramatically easier for customers to access the healthcare products and services they need to get and stay healthy. Towards this mission, we (Health Storefront and Shared Tech) are building the technology, products and services, that help customers find, buy, and engage with the healthcare solutions they need. Job summary We are seeking an exceptional Senior Applied Scientist to join a team of experts in the field of machine learning, and work together to break new ground in the world of healthcare to make personalized and empathetic care accessible, convenient, and cost-effective. We leverage and train state-of-the-art large-language-models (LLMs) and develop entirely new experiences to help customers find the right products and services to address their health needs. We work on machine learning problems for intent detection, dialogue systems, and information retrieval. You will work in a highly collaborative environment where you can pursue both near-term productization opportunities to make immediate, meaningful customer impacts while pursuing ambitious, long-term research. You will work on hard science problems that have not been solved before, conduct rapid prototyping to validate your hypothesis, and deploy your algorithmic ideas at scale. You will get the opportunity to pursue work that makes people's lives better and pushes the envelop of science. #everydaybetter Key job responsibilities - Translate product and CX requirements into science metrics and rigorous testing methodologies. - Invent and develop scalable methodologies to evaluate LLM outputs against metrics and guardrails. - Design and implement the best-in-class semantic retrieval system by creating high-quality knowledge base and optimizing embedding models and similarity measures. - Conduct tuning, training, and optimization of LLMs to achieve a compelling CX while reducing operational cost to be scalable. A day in the life In a fast-paced innovation environment, you work closely with product, UX, and business teams to understand customer's challenges. You translate product and business requirements into science problems. You dive deep into challenging science problems, enabling entirely new ML and LLM-driven customer experiences. You identify hypothesis and conduct rapid prototyping to learn quickly. You develop and deploy models at scale to pursue productizations. You mentor junior science team members and help influence our org in scientific best practices. About the team We are the Health AI team at HST (Health Store and Technology). The team consists of exceptional ML Scientists with diverse background in healthcare, robotics, customer analytics, and communication. We are committed to building and deploying the most advanced scientific capabilities and solutions for the products and services at Amazon Health.

Join the Amazon Web Services (AWS) Finance, Analytics, and Science Team! AWS is one of Amazon’s fastest growing businesses, serving millions of customers in more than 190 countries. We are reshaping the way global enterprises use information technology and we are powering the next generation of global business leaders. We are looking for entrepreneurial, analytical, creative, flexible leaders to help us redefine the information technology industry. If you want to join a fast-paced, innovative team that is making history, this is the place for you. As a Data Scientist, you will be expected to work directly with senior management on key business problems. Scientists at Amazon use statistical and ML models to address complex problems, design and test hypotheses, and contribute to the design of automated systems. We are looking for a results-driven scientist to join our team in Seattle. The right candidate will work closely with other scientists, business leaders, business intelligence engineers, and data engineers. The key strategic objectives for this role include: - Work with the AWS SMGS organization to provide data- and model-driven guidance and recommendations on business questions posed by leadership. - Interact with stakeholders, both technical and non-technical, to gather business requirements and translate them into concrete requirements for data science projects - Identify opportunities to measure and improve productivity with the end goal of driving growth. - Own data science projects end-to-end, demonstrating skill in defining key research questions, working with multiple data sources, evaluating competing models, and interpreting and communicating results. If you have an entrepreneurial spirit, you know how to deliver results fast, and you have a deeply quantitative, highly innovative approach to solving problems, we want to talk to you!

The People eXperience and Technology (PXT) Central Science Team uses economics, behavioral science, statistics, and machine learning to proactively identify mechanisms, process improvements and products, which simultaneously improve Amazon and the lives, wellbeing, and the value of work of 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 invest in innovation and rapid prototyping of scientific models, AI/ML technologies and software solutions to accelerate informed, accurate, and reliable decision backed by science and data. As a research scientist you will you will design and carry out surveys to address business questions; analyze survey and other forms of data with regression models; perform weighting and multiple imputation to reduce bias due to nonresponse. You will conduct methodological and statistical research to understand the quality of survey data. You will work with economists, engineers, and computer scientists to select samples, draft and test survey questions, calculate nonresponse adjusted weights, and estimate regression models on large scale data. You will evaluate, diagnose, understand, and surface drivers and moderators for key research streams, including (but are not limited to) attrition, engagement, productivity, inclusion, and Amazon culture. Key job responsibilities - Help to design and execute a scalable global content development and validation strategy to drive more effective decisions and improve the employee experience across all of Amazon - Conduct psychometric and econometric analyses to evaluate integrity and practical application of survey questions and data - Identify and execute research streams to evaluate how to mitigate or remove sources of measurement error - Partner closely and drive effective collaborations across multi-disciplinary research and product teams - Manage full life cycle of large-scale research programs (Develop strategy, gather requirements, manage and execute)

Are you passionate about AI for recommendation systems? Do you want to influence the content that customers see at Amazon.com? Our recommendation services team designs and implements scalable machine learning solutions to personalize and optimize customer experience across Amazon retail pages. We are currently expanding in New York, and are looking for an applied scientist to join us in this exciting journey. As an Applied Scientist, you will: - Push the boundaries of real-world ranking, recommendation, and optimization systems - Support science, engineering and product development on a scale only seen at Amazon. - Champion and define best practices to maximize learnings while mentoring more junior scientists and engineers. - Obsess over customer needs and satisfaction. - Create intellectual property, influence others while demonstrating significant creativity and being vocally self-critical. - Shape product definitions and objective and surface signals on how these objectives meet long term customer needs. - Translate metrics & signals into actionable plans to calibrate individual components. - Operate hands-on and as an implementor of algorithms and models delivered to production systems. - Help define customer focused research initiatives. Please visit https://www.amazon.science for more information.

Are you interested in shaping the future of entertainment? Prime Video's technology teams are creating best-in-class digital video experience. As a Prime Video technologist, you’ll have end-to-end ownership of the product, user experience, design, and technology required to deliver state-of-the-art experiences for our customers. You’ll get to work on projects that are fast-paced, challenging, and varied. You’ll also be able to experiment with new possibilities, take risks, and collaborate with remarkable people. We’ll look for you to bring your diverse perspectives, ideas, and skill-sets to make Prime Video even better for our customers. With global opportunities for talented technologists, you can decide where a career Prime Video Tech takes you! We are looking for passionate, hard-working, and talented individuals to help us push the envelope of content localization. We work on a broad array of research areas and applications, including but not limited to multimodal machine translation, speech synthesis, speech analysis, and asset quality assessment. Candidates should be prepared to help drive innovation in one or more areas of machine learning, audio processing, and natural language understanding. Key job responsibilities We prefer candidates with experience in audio processing, natural language understanding and machine learning. Familiarity with foundational models, speech synthesis and machine translation will be a plus. The candidate should be a strong communicator, able to describe scientifically rigorous work to business stakeholders of varying levels of technical sophistication. Strong inter-personal and mentoring skills to develop applied science talent in the team is another important requirement. The candidate will closely partner with the solution development teams, and should be intensely curious about how the research is moving the needle for business. About the team Prime Video offers customers a vast collection of movies, series, and sports—all available to watch on hundreds of compatible devices. U.S. Prime members can also subscribe to 100+ channels including Max, discovery+, Paramount+ with SHOWTIME, BET+, MGM+, ViX+, PBS KIDS, NBA League Pass, MLB.TV, and STARZ with no extra apps to download, and no cable required. Prime Video is just one of the savings, convenience, and entertainment benefits included in a Prime membership. More than 200 million Prime members globally enjoy access to Amazon’s enormous selection, exceptional value, and fast delivery.