Careers

At AWS Health AI, we leverage AI to revolutionize healthcare and if you are passionate to make a global-scale difference in Health, we have an opportunity for you. AWS Health AI is seeking a inventive and talented Applied Scientist to join forces in the area of Natural Language Processing, Genomics, Medical Imaging or Biomedical. We are on a mission to use Gen-AI and build new innovative solutions for Healthcare and Life Sciences users. You will be involved in the entire product development cycle including customer discovery, experimentation, design, prototyping. Whats cool? You will collaborate with team of ML-focused SDEs to productionalize these solutions. Our ideal candidates thrives in ambiguity, build collaborative relationships, moves fast, and are passionate about meaningful work. They will have the technical skills to design and build complex distributed systems that runs at AWS scale. They prefer working on small, focused teams, own their product, and love to pitch in anywhere to get the job done. They lead by example and the team naturally gravitate towards them because of their engineering expertise and decision-making ability. They can communicate effectively with a wide variety of audiences and are comfortable pitching new ideas. We are looking for candidates who thrive in an exciting, fast-paced environment and who have a strong personal interest in learning, researching, and creating new technologies with high customer impact. You will have an opportunity to influence product and leaders. As an Applied Scientist you will partner with talented scientists and engineers to design, train, test, and deploy machine learning models. You will contribute to innovative features, improve our services based on customer requirements and help maintain a highly scalable data and model management infrastructure that supports cutting-edge research. You will be responsible for translating business and engineering requirements into deliverables and software products. Prior domain knowledge in speech, natural language processing, or computer vision is strongly preferred; solid knowledge of fundamentals of statistics, machine learning, and deep learning is required. Candidates should possess strong software engineering skills and several years of industry experience. Key job responsibilities - Applying latest deep learning and natural language processing techniques to ship new features for our customer - Convert ambiguous business questions into precise science problems - Regularly ship deep learning models and natural language processing models that run at AWS scale - Collaborate with engineers, clinical experts and product managers to deliver your solutions What You'll Do: * Collaborate with a team of Clinical experts, researchers and engineers in solving complex healthcare challenges * Develop novel algorithms and modeling techniques for multimodal systems * Apply latest deep learning, Gen AI and natural language processing techniques to build model-based solutions in Health domain * Collaborate with cross-functional teams to create impactful products and services. Convert ambiguous business questions into precise science problem, and share insights/learnings from your experimentation to help product direction. * Conduct cutting-edge research and publish in top-tier conferences and journals What We're Looking For: * Strong background in deep learning and multimodal systems * Passion for applying AI to healthcare challenges * Ability to lead and mentor research teams * Experience in developing scalable, secure AI/ML systems * Expertise in areas such as medical imaging, medical notes, ontologies, genomics, or clinical decision support About the team This team is responsible for building classical as well as GenAI solutions that directly integrate as solutions for HealthCare and Life Science users. 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. 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.

The Worldwide Defect Elimination (WWDE) Science team in Amazon Customer Service builds state-of-the-art Artificial Intelligence (AI) models to enable defect-free shopping experiences for Amazon customers. We develop technology and mechanisms to discover, root cause, measure, and escalate defects for resolution before they impact a broader range of customers. We are looking for a creative problem solver and technically-skilled Applied Scientist able and interested in building AI solutions to address customer issues at scale. The ideal candidate will lead the development of innovative solutions that identify, root cause, attribute, and summarize problems embedded in large volumes of customer feedback in different modalities. They will also utilize the latest advances in GenAI technology to explore billions of customer contacts and automate defect resolution workflows. As a part of this role, this candidate will collaborate with a large team of experts in the field and move the state of defect elimination research forward. This candidate should have a knack for leveraging AI to translate complex data insights into actionable strategies and can communicate these effectively to both technical and non-technical audiences. Key job responsibilities * Apply science models to extract actionable information from large volumes and varying modalities of customer feedback * Leverage GenAI/Large Language Model (LLM) technology for scaling and automating defect elimination 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 A day in the life 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! Amazon offers a full range of benefits that support you and eligible family members, including domestic partners and their children. 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 About the team The Worldwide Defect Elimination (WWDE) team's mission is to understand and resolve all issues impacting customers at scale. The WWDE Science team is a force multiplier within this group, helping to to apply science solutions to eliminate defects and enhance customer experience.

The Alexa AI team is seeking a talented, self-driven Senior Applied Scientist to work on prototyping, optimizing, and deploying ML algorithms within the realm of Generative AI. Key job responsibilities - Research, experiment and build Proof Of Concepts advancing the state of the art in AI & ML for GenAI. - Collaborate with cross-functional teams to architect and execute technically rigorous AI projects. - Thrive in dynamic environments, adapting quickly to evolving technical requirements and deadlines. - Engage in effective technical communication (written & spoken) with coordination across teams. - Conduct thorough documentation of algorithms, methodologies, and findings for transparency and reproducibility. - Publish research papers in internal and external venues of repute - Support on-call activities for critical issues A day in the life This Senior Applied Scientist will be working with a group of talented scientists on researching algorithm and running experiments to test scientific proposal/solutions in LLMs. They will also collaborate with partner teams across roles (product/program managers, data annotators, developers, etc) to deliver robust models in production. They will mentor other scientists, review and guide their work, and help develop roadmaps for the team. They will work closely with partner teams to deliver platform features that require cross-team leadership.

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 Health Economics and Health Outcomes Research to work together to break new ground in the world of healthcare to make personalized and empathetic care accessible, convenient, and cost-effective. You will build and deploy state-of-the-art ML models for individual customer and population-level outcomes. You will work with clinical, product, and finance partners to test and deploy models to develop new product offerings and recommend solutions to address customer health care needs. 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, Finance and Clinical business and healthcare problems into scientific questions - Build and leverage data pipelines for training and evaluating ML models - Design, implement, and optimize the best-in-class machine learning solutions for forecasting and behavior change - Design and conduct live experiments to validate model performance - Deploy ML solutions into existing and new customer-facing systems and business processes A day in the life In a fast-paced innovation environment, you work closely with product, finance, and clinical teams to understand customer's and business challenges. You translate product and business requirements into science problems. You dive deep into challenging science problems, access and analyze data, and enabling new ML solutions to impact 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 Measurement Science team at HST (Health Store and Technology). The team consists of Scientists and Economists with experience in varied industries, including health care. We are committed to building and deploying the most advanced scientific capabilities and solutions for the products and services at Amazon Health.

Amazon has the world’s most complex supply chain: we fulfill global demand for hundreds of millions of products at lightning fast delivery speeds. A core part of the operations is forecasting: We forecast the demand of hundreds of millions of products up to a year into the future. The forecasts are used to automatically order hundreds of millions worth of inventory weekly, decide where to place that inventory, and to establish labor plans for hundreds of warehouses. The Applied Scientist II will work with the Supply Chain Optimization Technologies (SCOT) Forecasting team and both business and engineering stakeholders worldwide to develop state of art machine learning models to forecast inbound shipment. The scientist develops novel algorithmic architectures, toward the ultimate goal of accurately predicting when and how Amazon receives shipments of millions of products world-wide. This drives down costs and enables the offer of lower prices and better in-stock selection for our customers. Working collaboratively, you will develop solutions to complex problems, such as designing the next generation of algorithms. As an Applied Scientist, you will continue to contribute to the research community, by working with other scientists across Amazon, as well as collaborating with academic researchers and publishing papers. Within SCOT Forecasting, our Science community values teamwork and recognizes the need to take chances and try new ideas that may fail. Furthermore, our builder culture means that Scientists and Software Development Engineers work closely together to invent and construct at a massive scale. Your work can be part of Amazon production system and result in concrete business impact. Key job responsibilities - Design, implement, and evaluate innovative models, agents, and software prototypes. - Collaborate with a team of experienced scientists to drive technological advancements. - Develop novel solutions to complex business problems in collaboration with partner teams. - Constructively critique peer research and mentor junior scientists and engineers - Contribute to Amazon's global science community through collaboration and publication of groundbreaking research. About the team Supply Chain Optimization Technologies (SCOT) owns Amazon’s global inventory planning systems. We decide what, when, where, and how much we should buy to meet Amazon’s business goals and to make our customers happy. We decide how to place and move inventory within Amazon’s fulfillment network. We do this for hundreds of millions of items and hundreds of product lines worth billions of dollars of world-wide. Venturing beyond traditional operations research methods for sequential decision-making in inventory planning. The team combines empirical research and real world testing, backed by a robust theoretical foundation.

Amazon Advertising is one of Amazon's fastest growing businesses. Amazon's advertising portfolio helps merchants, retail vendors, and brand owners succeed via native advertising, which grows incremental sales of their products sold through Amazon. The primary goals are to help shoppers discover new products they love, be the most efficient way for advertisers to meet their business objectives, and build a sustainable business that continuously innovates on behalf of customers. Our products and solutions are strategically important to enable our Retail and Marketplace businesses to drive long-term growth. We deliver billions of ad impressions and millions of clicks and break fresh ground in product and technical innovations every day! The Creative X team within Amazon Advertising time aims to democratize access to high-quality creatives (audio, images, videos, text) by building AI-driven solutions for advertisers. To accomplish this, we are investing in understanding how best users can leverage Generative AI methods such as latent-diffusion models, large language models (LLM), generative audio (music and speech synthesis), computer vision (CV), reinforced learning (RL) and related. As an Applied Scientist you will be part of a close-knit team of other applied scientists, engineers and product managers who are highly collaborative and at the top of their respective fields. We are looking for talented Applied Scientists who are adept at a variety of skills, especially at the interface of how users can use state-of-the-art generative music and audio, computer vision, latent diffusion or related foundational models that will accelerate our plans to generate high-quality creatives on behalf of advertisers. Every member of the team is expected to build customer (advertiser) facing features, contribute to the collaborative spirit within the team, publish, patent, and bring cutting edge research to raise the bar within the team. You will: - Drive the invention and development of novel methods for the use of Generative AI in ads - Work closely and integrate end-to-end proof-of-concept Machine Learning projects that have a high degree of ambiguity, scale and complexity. - Build interface-oriented systems that use Machine Learning models, perform proof-of-concept, experiment, optimize, and deploy your models into production; work closely with software engineers to assist in productionizing your ML models. - Run A/B experiments, gather data, and perform statistical analysis. - Establish scalable, efficient, automated processes for large-scale data analysis, machine-learning model development, model validation and serving. - Mentor and help recruit Applied Scientists to the team. - Present results and explain methods to senior leadership. - Willingness to publish research at internal and external top scientific venues. - Write and pursue IP submissions. Key job responsibilities This role is focused on developing Machine Learning and Generative AI methods to augment generative imagery and videos. You will develop new paradigms that will impact how users can engage and benefit from GenAI and that are at the core of advertising-facing tools that we are launching. You will also work on development of ML and GenAI models. You will conduct literature reviews to stay on the cutting edge of the field. You will regularly engage with product managers, who will partner with you to productize your work. A day in the life On a day-to-day basis, you will be doing your independent research and work to develop models, you will participate in sprint planning, collaborative sessions with your peers, and demo new models and share results with peers, other partner teams and leadership. About the team The team is a growing team of applied scientists and product leaders. We reside in the Creative X organization, which focuses on creating products for advertisers that will improve the quality of the creatives within Amazon Ads. We are open to hiring candidates to work out of one of the following locations: UK (London)

Device Economics is looking for an economist experienced in causal inference, empirical industrial organization, forecasting, and scaled systems to work on business problems to advance critical resource allocation and pricing decisions in the Amazon Devices org. Output will be included in scaled systems to automate existing processes and to maximize business and customer objectives. Amazon Devices designs and builds Amazon first-party consumer electronics products to delight and engage customers. Amazon Devices represents a highly complex space with 100+ products across several product categories (e-readers [Kindle], tablets [Fire Tablets], smart speakers and audio assistants [Echo], wifi routers [eero], and video doorbells and cameras [Ring and Blink]), for sale both online and in offline retailers in several regions. The space becomes more complex with dynamic product offering with new product launches and new marketplace launches. The Device Economics team leads in analyzing these complex marketplace dynamics to enable science-driven decision making in the Devices org. Device Economics achieves this by combining economic expertise with macroeconomic trends, and including both in scientific applications for use by internal analysts, to provide deep understanding of customer preferences. Our team’s outputs inform product development decisions, investments in future product categories, product pricing and promotion, and bundling across complementary product lines. We have achieved substantial impact on the Devices business, and will achieve more. Device Economics seeks an economist adept in measuring customer preferences and behaviors with proven capacity to innovate, scale measurement, and drive rigor. The candidate must be passionate about advancing science for business and customer impact.

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), and Text and Multimodal Search and Question 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 We are seeking an Applied Scientist who will work in areas related to Information Retrieval, including Neural Information Retrieval, as well as Answer Generation from the retrieved results, using Generative LLMs. 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, to interact with other Scientists on the same project and on relateed projects. The Applied Scientist will regularly interact with Engineering and Product partners and needs excellent communication skills to effectively collaborate with colleagues with different backgrounds and skill sets. The Applied Scientist will engage in long-term projects, and, at the same time, as the need arises, will dive deep in customer issues, provide suggestions to Engineering for short term mitigation, and formulate principled solutions for longer term investigation.. We expect that an Applied Scientist engage sthe Science community within and beyond Amazon, actively publishes their work, either as patents or as scientific papers at top-tier conferences. 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.

Do you want to join an innovative team of scientists who use machine learning and statistical techniques to help Amazon provide the best customer experience by preventing eCommerce fraud? 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? Do you like to own end-to-end business problems/metrics and directly impact the profitability of the company? Do you enjoy collaborating in a diverse team environment? If yes, then you may be a great fit to join the Amazon Buyer Risk Prevention (BRP) Machine Learning group. We are looking for a talented scientist who is passionate to build advanced algorithmic systems that help manage safety of millions of transactions every day. Key job responsibilities Use machine learning and statistical techniques to create scalable risk management systems Learning and understanding large amounts of Amazon’s historical business data for specific instances of risk or broader risk trends Design, development and evaluation of highly innovative models for risk management Working closely with software engineering teams to drive real-time model implementations and new feature creations Working closely with operations staff to optimize risk management operations, Establishing scalable, efficient, automated processes for large scale data analyses, model development, model validation and model implementation Tracking general business activity and providing clear, compelling management reporting on a regular basis Research and implement novel machine learning and statistical approaches

Do you want to join an innovative team of scientists who use machine learning and statistical techniques to help Amazon provide the best customer experience by preventing eCommerce fraud? 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? Do you like to own end-to-end business problems/metrics and directly impact the profitability of the company? Do you enjoy collaborating in a diverse team environment? If yes, then you may be a great fit to join the Amazon Buyer Risk Prevention (BRP) Machine Learning group. We are looking for a talented scientist who is passionate to build advanced algorithmic systems that help manage safety of millions of transactions every day. Key job responsibilities Use machine learning and statistical techniques to create scalable risk management systems Learning and understanding large amounts of Amazon’s historical business data for specific instances of risk or broader risk trends Design, development and evaluation of highly innovative models for risk management Working closely with software engineering teams to drive real-time model implementations and new feature creations Working closely with operations staff to optimize risk management operations, Establishing scalable, efficient, automated processes for large scale data analyses, model development, model validation and model implementation Tracking general business activity and providing clear, compelling management reporting on a regular basis Research and implement novel machine learning and statistical approaches