Careers

Amazon’s eCommerce Foundation (eCF) organization provides the core technologies that drive and power Amazon's Stores, Digital, and Other (SDO) businesses. Millions of customer page views and orders per day are enabled by the systems eCF builds from the ground up. CloudTune, within eCF, empowers growth and business agility needs by automatically and efficiently managing AWS capacity and business processes needed to safely meet Amazon’s customer demand. CloudTune serves its primary customers, internal software teams, through forecast driven automation of cost controllership, capacity management and scaling. We predict expected load, and drive procurement and allocation of AWS capacity for new product launches and high velocity events like Prime Day and Cyber Monday. CloudTune, in partnership with Region Flexibility, is driving an SDO-wide program to diversify our use of AWS regions beyond DUB, IAD, and PDX regions. The objective of the Diversify AWS Region Usage (DARU) program is to mitigate the risk of capacity concentration by encouraging teams to design workloads that are region-flexible, utilize AWS automation such as Flexible Fleets to access multiple capacity pools, and optimize workload placement so SDO efficiently utilizes AWS. This is a strategic, highly visible, multi-year program which spans all Amazon business. CloudTune is looking for an experienced Applied Scientist to join our forecasting team and support DARU program. The team develops sophisticated algorithms that involve learning from large amounts of past data, such as actual sales, website traffic, merchandising activities, promotions, similar products and product attributes to forecast the demand for our compute infrastructure. These forecasts are used to determine the level of investment in capital expenditures, promotional activity, engineering efficiency projects and determining financial performance. As a Senior Scientist in CloudTune, you will work with other scientists, software engineers, data engineers, and product managers on a variety of important applied machine learning problems in the area of time series modeling. You will work on statistical problems with a high level of ambiguity. You will analyze and process large amounts of data, develop new algorithms and improve existing approaches based on statistical models, machine learning algorithms and big data solutions to automatically scale Amazon’s compute infrastructure, optimizing the balance between availability risk and cost efficiency for all of Amazon businesses. Key job responsibilities • Process and analyze large data sets, mining additional data sources as needed • Analyze compute scaling metrics to identify business drivers that influence infrastructure expenditures • Build statistical models and drive scalable solutions for multi-year capacity demand forecasting horizons • Prototype these models by using high-level modeling languages such as R or Python • Create, enhance, and maintain technical documentation, and present to other scientists and business leaders We are open to hiring candidates to work out of one of the following locations: Seattle, WA, USA

AWS Infrastructure Services owns the design, planning, delivery, and operation of all AWS global infrastructure. In other words, we’re the people who keep the cloud running. We support all AWS data centers and all of the servers, storage, networking, power, and cooling equipment that ensure our customers have continual access to the innovation they rely on. We work on the most challenging problems, with thousands of variables impacting the supply chain — and we’re looking for talented people who want to help. You’ll join a diverse team of software, hardware, and network engineers, supply chain specialists, security experts, operations managers, and other vital roles. You’ll collaborate with people across AWS to help us deliver the highest standards for safety and security while providing seemingly infinite capacity at the lowest possible cost for our customers. And you’ll experience an inclusive culture that welcomes bold ideas and empowers you to own them to completion. Are you an experienced in sustainability science professional who is passionate about making a big impact? Are you interested in a high impact role at the world’s preeminent cloud computing company? The AWS Sustainability Science team is hiring a Sustainability Scientist. This role will support our Climate Pledge goal of net zero carbon by 2040 by developing scalable methods and models to assess and improve the environmental impacts of AWS data centers and cloud computing services from manufacturing, transportation, use, and end-of-life. This work will drive a deeper understanding of AWS’s environmental impacts, and enable strategic management of our carbon emissions. The ideal candidate will have industry experience in driving Life Cycle Assessments (LCAs) of products and services, possess a strong understanding of the GHG Protocol and carbon accounting practices, and have a detailed knowledge of manufacturing, design, development, and/or sourcing. The candidate should be comfortable working with imperfect data, identifying sources of uncertainty, and finding public data to fill the gaps where needed. The successful candidate must have strong analytical skills and the ability to apply systems thinking to complex, fast moving problems. The candidate should have familiarity with LCA methods and applications. The successful candidate will act as a subject matter expert, including designing research, gathering data, interpreting results, and developing metrics and reports. The candidate will coordinate with cross-functional project teams in gathering and analyzing large amounts of data. Key job responsibilities In this role you will be responsible for: * Serving as an AWS subject matter expert in Sustainability * Developing Life Cycle Assessment (LCA) methodologies to ensure AWS has an accurate and credible basis for sustainability efforts. * Developing internal LCA models for AWS infrastructure and services including server hardware and mechanical and electrical systems * Conducting LCAs including research, data collection, modeling, data analysis, data visualization, and reporting to quantify environmental impacts of our data centers and cloud computing services * Developing reports, dashboards and metrics which distill complex data into actionable insights to inform improvements * Building and developing relationships with internal and external stakeholders to drive programs to completion * Work closely with software engineering teams to drive real-time model implementations and new features * Having fun and working hard! A day in the life Each day you will interact with different teams responsible for all aspects of hardware and data centers. Your work will span the life cycle of our operations and allow you to influence how we develop and implement sustainability practices. You will have the opportunity to work on projects locally and globally. About the team 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 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. 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. We are open to hiring candidates to work out of one of the following locations: Arlington, VA, USA | Seattle, WA, USA

AWS Infrastructure Services owns the design, planning, delivery, and operation of all AWS global infrastructure. In other words, we’re the people who keep the cloud running. We support all AWS data centers and all of the servers, storage, networking, power, and cooling equipment that ensure our customers have continual access to the innovation they rely on. We work on the most challenging problems, with thousands of variables impacting the supply chain — and we’re looking for talented people who want to help. You’ll join a diverse team of software, hardware, and network engineers, supply chain specialists, security experts, operations managers, and other vital roles. You’ll collaborate with people across AWS to help us deliver the highest standards for safety and security while providing seemingly infinite capacity at the lowest possible cost for our customers. And you’ll experience an inclusive culture that welcomes bold ideas and empowers you to own them to completion. Are you an experienced in sustainability science professional who is passionate about making a big impact? Are you interested in a high impact role at the world’s preeminent cloud computing company? The AWS Sustainability Science team is hiring a Sr. Sustainability Scientist. This role will support our Climate Pledge goal of net zero carbon by 2040 by developing scalable methods and models to assess and improve the environmental impacts of AWS data centers and cloud computing services from manufacturing, transportation, use, and end-of-life. This work will drive a deeper understanding of AWS’s environmental impacts, and enable strategic management of our carbon emissions. The ideal candidate will have industry experience in driving Life Cycle Assessments (LCAs) of products and services, possess a strong understanding of the GHG Protocol and carbon accounting practices, and have a detailed knowledge of manufacturing, design, development, and/or sourcing. The candidate should be comfortable working with imperfect data, identifying sources of uncertainty, and finding public data to fill the gaps where needed. The successful candidate must have strong analytical skills and the ability to apply systems thinking to complex, fast moving problems. The candidate should have familiarity with LCA methods and applications. The successful candidate will act as a subject matter expert, including designing research, gathering data, interpreting results, and developing metrics and reports. The candidate will coordinate with cross-functional project teams in gathering and analyzing large amounts of data. Key job responsibilities In this role you will be responsible for: * Serving as an AWS subject matter expert in Sustainability * Developing Life Cycle Assessment (LCA) methodologies to ensure AWS has an accurate and credible basis for sustainability efforts. * Developing internal LCA models for AWS infrastructure and services including server hardware and mechanical and electrical systems * Conducting LCAs including research, data collection, modeling, data analysis, data visualization, and reporting to quantify environmental impacts of our data centers and cloud computing services * Developing reports, dashboards and metrics which distill complex data into actionable insights to inform improvements * Building and developing relationships with internal and external stakeholders to drive programs to completion * Work closely with software engineering teams to drive real-time model implementations and new features * Having fun and working hard! A day in the life Each day you will interact with different teams responsible for all aspects of hardware and data centers. Your work will span the life cycle of our operations and allow you to influence how we develop and implement sustainability practices. You will have the opportunity to work on projects locally and globally. About the team 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 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. 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. We are open to hiring candidates to work out of one of the following locations: Arlington, VA, USA | Seattle, WA, USA

This position involves developing advanced ML/DL models that continually improve Prime Video's Content Adaptive Encoding (CAE) practices for Video-on-demand (VoD) streaming use-case. You will work closely with subject matter experts (Research Scientists) with depth in the video encoding/quality/processing areas to maximize the video quality that Prime Video customers experience under a given network condition. Your work would directly influence the customer experience and will also help drive efficiency related business goals. The work would involve working with creation and cleaning of ground-truth datasets driving the model, feature engineering, development of classification or regression ML/DL models with high accuracy, optimization and deployment of such models in production workflow, and defining/measuring suitable at-scale success criteria. Key job responsibilities You would develop ML/DL based classification/regression models based on content properties across the processing chain involved in encoding, including changes within modern encoders to reduce run-time or to improve the level of adaptation to content properties. You would work across multiple codecs including next-gen codecs, standard and High Dynamic range content. Aspects of work can involve scene understanding at a semantic level using latest techniques. You would develop innovative solutions that achieve the best balance between speed vs performance. You would work under the guidance of research scientists. You would conduct subjective ratings tests to generate ground truth data for your models, when required. You would develop novel approaches to perform fast searches in high dimensional parameter space. You would contribute to development of new video quality models that correlate highly with subjective ratings. A day in the life You will work with L5-L8 Research Scientists within the team who will bring the specific problem definition required to set and meet annual goals, 3Y/5Y roadmap items. You will work with University partners who help PV explore new problem areas. You will interface with SDEs to convert the output of the research team into production workflows. You will develop new AI workflows that are more efficient from a compute perspective. You will write disclosures capturing innovative ideas in realizing low complexity, highly performant ML/DL methods and will then publish papers in internal and external conferences. About the team Our mission is to build and operate the most innovative video streaming technology stack that provides the best customer-centric streaming experience for VOD and Live globally and supports all business use cases (subscription, transactional, ad-supported). We invent and implement technologies that deliver a flawless, engaging streaming experience for our customers, using the fewest bits possible. We commit to our values of respect and integrity by creating a work environment that is supportive, diverse, inspiring, and inclusive. We are open to hiring candidates to work out of one of the following locations: Bangalore, KA, IND

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 We are open to hiring candidates to work out of one of the following locations: Seattle, WA, USA

Amazon Advertising is one of Amazon's fastest growing and most profitable businesses, responsible for defining and delivering a collection of advertising products that drive discovery and sales. As a core product offering within our advertising portfolio, Sponsored Products (SP) helps merchants, retail vendors, and brand owners succeed via native advertising, which grows incremental sales of their products sold through Amazon. The SP team's 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! Does serving ads to billions of search requests daily and finding the most relevant ads for a search page from billions of ads in 10s of milliseconds excite you? The Sponsored Products Demand Utilization team owns finding the appropriate ads to surface to customers when they search for products on Amazon. We strive to understand our customers’ intent and identify relevant ads which enable them to discover new and alternate products. This also enables sellers on Amazon to showcase their products to customers, which may at times be buried deeper in the search results. Our systems and algorithms operate on one of the world's largest product catalogs, matching shoppers with products - with a high relevance bar and strict latency constraints. We are a team of machine learning scientists and software engineers working on complex solutions to understand the customer intent and present them with ads that are not only relevant to their actual shopping experience, but also non-obtrusive. This area is of strategic importance to Amazon Retail and Marketplace business, driving long term-growth. We are looking for an Applied Scientist, with a background in Machine Learning to optimize serving ads on billions of product pages. The solutions you create would drive step increases in coverage of sponsored ads across the retail website and ensure relevant ads are served to Amazon's customers. You will directly impact our customers’ shopping experience while helping our sellers get the maximum ROI from advertising on Amazon. You will be expected to demonstrate strong ownership and should be curious to learn and leverage the rich textual, image, and other contextual signals. This role will challenge you to utilize cutting-edge machine learning techniques in the domain of predictive modeling, natural language processing (NLP), deep learning, reinforcement learning, query understanding, vector search (kNN) and image recognition to deliver significant impact for the business. Ideal candidates will be able to work cross functionally across multiple stakeholders, synthesize the science needs of our business partners, develop models to solve business needs, and implement solutions in production. In addition to being a strongly motivated IC, you will also be responsible for mentoring junior scientists and guiding them to deliver high impacting products and services for Amazon customers and sellers. Why you will love this opportunity: Amazon is investing heavily in building a world-class advertising business. This team defines and delivers a collection of advertising products that drive discovery and sales. Our solutions generate billions in revenue and drive long-term growth for Amazon’s Retail and Marketplace businesses. We deliver billions of ad impressions, millions of clicks daily, and break fresh ground to create world-class products. We are a highly motivated, collaborative, and fun-loving team with an entrepreneurial spirit - with a broad mandate to experiment and innovate. Impact and Career Growth: You will invent new experiences and influence customer-facing shopping experiences to help suppliers grow their retail business and the auction dynamics that leverage native advertising; this is your opportunity to work within the fastest-growing businesses across all of Amazon! Define a long-term science vision for our advertising business, driven from our customers' needs, translating that direction into specific plans for research and applied scientists, as well as engineering and product teams. This role combines science leadership, organizational ability, technical strength, product focus, and business understanding. Team video https://youtu.be/zD_6Lzw8raE Key job responsibilities As an Applied Scientist on this team, you will: - Drive end-to-end Machine Learning projects that have a high degree of ambiguity, scale, complexity. - Perform hands-on analysis and modeling of enormous data sets to develop insights that increase traffic monetization and merchandise sales, without compromising the shopper experience. - Build machine learning models, perform proof-of-concept, experiment, optimize, and deploy your models into production; work closely with software engineers to assist in deploying 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. - Research new and innovative machine learning approaches. We are open to hiring candidates to work out of one of the following locations: Arlington, VA, USA

Amazon is looking for a talented Postdoctoral Scientist to join our Perfect Order Experience (POE), Trustworthy Shopping Experience (TSE) team for a one-year, full-time research position. Postdoctoral Scientists will drive data-driven innovations in decision optimization and causal inference. In this role, you will have the opportunity to: - Leverage advanced statistical techniques and machine learning models to extract valuable insights from historical data and comparable item information. - Tackle data scarcity challenges by developing innovative approaches to maximize the utility of available data sources. - Collaborate with cross-functional teams to develop and deploy production-ready solutions. - Participate in research activities, including publishing papers, attending conferences, and collaborating with academic institutions to advance the state-of-the-art in relevant fields. 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. About the team We are a Center of Excellence of building economic solutions to optimize the return of investment at the program level and at the decision level. We focus on projects that have the largest impact and greatest long term potential across the business. Our products are models, scalable services and actionable insights. We proactively identify and explore opportunities on behalf of our business partners. We are open to hiring candidates to work out of one of the following locations: Seattle, WA, USA

Are you excited about improving Amazon's next generation robotic storage systems through modeling and simulation? Are you looking for opportunities to apply this expertise on real problems at truly vast scale? At Amazon Fulfillment Technologies and 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. We are looking for enthusiastic scientists for a variety of roles. The Research team at Amazon Robotics is seeking a passionate, collaborative, hands-on Research Scientist to quantify the performance of Amazon's next generation robotic warehouse concepts through simulation modeling and analysis. The focus of this position is to simulate multiple concepts and scenarios to provide insights to solution designers to help down-select options and solidify the design. It includes modelling new robotic systems and workflows, and applying statistical methods to analyze outcomes. This work spans from mathematical modelling, to statistical analysis, to concept simulation, to software-in-the-loop simulation, to running large-scale A/B tests on robots in our facilities. The ideal candidate for this position will be familiar with statistical analysis and mathematical modeling techniques 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 * Mathematical modeling - Building mathematical models to describe early stage concepts to help down-select the design prior to simulation modeling and analysis. * Input curation and validation - derive suitable inputs for simulation through a combination of historical data, data augmentation, and synthetic data generation where appropriate. Validate the suitability of these inputs for the analysis of interest. * Simulation analysis - Insights from simulation data or ad-hoc experimentation using statistical methodologies. * Research delivery - Proving/dis-proving strategies in offline data or in simulation A day in the life On a typical day in this role you will work to progress your research projects, meet with engineering, systems, and solutions stakeholders, brainstorm with other scientists on the team, and participate in team processes. You will follow your modeling and simulation projects though the entire life cycle of design, implementation, evaluation, analysis, and will communicate your findings and results through technical papers and reports. You will consult with engineering teams as they incorporate your models and analyses into system and process designs. 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 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 Our multi-disciplinary science team includes scientists with backgrounds in simulation, planning and scheduling, grasping and manipulation, machine learning, and operations research. We develop novel planning algorithms and machine learning methods and apply them to real-word robotic warehouses, including: * Planning and coordinating the paths of thousands of robots * Dynamic allocation and scheduling of tasks to thousands of robots * Learning how to adapt system behavior to varying operating conditions * Co-design of robotic logistics processes and the algorithms to optimize them Our team also serves as a hub to foster innovation and support scientists across Amazon Robotics. We also coordinate research engagements with academia, such as the Robotics section of the Amazon Research Awards. We are open to hiring candidates to work out of one of the following locations: North Reading, MA, USA

Amazon Advertising is one of Amazon's fastest growing and most profitable businesses, responsible for defining and delivering a collection of advertising solutions that drive product discovery and sales. We deliver billions of ad impressions every single day on behalf of our advertisers. You'll work with us to help our Advertising teams make sense of the torrent of data produced by the advertising lifecycle. We are using cutting edge generative AI to help teams generate insights faster based on our massive data lake. You will need to invent new techniques for metrics retrieval and SQL generation to ensure we're retrieving accurate and trusted data. You'll create feedback loops to ensure our solution is constantly evaluating itself and improving. Being that this is for a conversational AI position, here is what our bot replied when we prompted it for a job description of who should help build it: Role Overview: We are looking for an exceptional applied scientist to join our team building SpektrBot, a conversational AI assistant that helps data engineers and analysts with their workflows. You will work closely with engineers and product managers to design, implement, and optimize natural language processing models like intent classification, named entity recognition, question answering, etc. that enable our Ads chatbot to understand user requests and have natural conversations. Responsibilities: - Study and understand data engineering and analytics workflows to design the right conversational experiences - Research, design, and develop NLP/NLU models for intent classification, entity extraction, sentiment analysis etc. - Continuously improve models through techniques like active learning, transfer learning etc. - Optimize models for metrics like precision, recall, latency, interpretability etc. - Implement models within overall bot architecture and integrate with backend systems - Collaborate with engineers to productionize and monitor models - Stay up-to-date on latest advancements in conversational AI research, specifically in LLMs (multi-agent, chain of thought, autonomous agents) - Be familiar with optimizing retrievers in RAG architectures. Key job responsibilities You will test multiple foundational models and fine tune when appropriate. You will create feedback loops that will evaluate performance and improve our systems. You will optimize prompts for better responses from our LLMs. You will build tools to auto-curate metadata using LLMs. A day in the life You will invent new experiences and influence customer-facing shopping experiences to help suppliers grow their retail business and the auction dynamics that leverage native advertising; this is your opportunity to work within the fastest-growing businesses across all of Amazon! Define a long-term science vision for our advertising business, driven from our customers' needs, translating that direction into specific plans for research and applied scientists, as well as engineering and product teams. This role combines science leadership, organizational ability, technical strength, product focus, and business understanding. About the team We have a small scrappy team carved out from a large Ads wide data lake team. We are swimming in petabytes of data that we help the organization make sense of. Our team's mission is to help anyone in the Ads org find the data they need using only natural language. We are a supportive and collaborative team who iterates quickly and shares in each others' successes. We are open to hiring candidates to work out of one of the following locations: Seattle, WA, USA

Amazon is seeking a passionate, talented, and inventive Applied Scientist with a strong machine learning background and familiarity with LLMs to help build automated insights and generative AI tools to accelerate our customers' journey to the cloud. This is a high-visibility role with significant impact potential. About you: You, as the right candidate, are adept at executing every stage of the machine learning development life cycle in a business setting; from initial requirements gathering to through final model deployment, including adoption measurement and improvement. You will be working with large volumes of structured and unstructured data spread across multiple databases and can design and implement data pipelines to clean and merge these data for research and modeling. You will invent, implement, and deploy state of the art machine learning and generative AI algorithms and systems. You will build prototypes and explore conceptually large scale ML solutions. You will interact closely with our customers and with the academic community. Beyond mathematical understanding, you have a deep intuition for machine learning algorithms that allows you to translate business problems into the right machine learning, data science, and/or statistical solutions. You’re able to pick up and grasp new research and identify applications or extensions within the team. You’re talented at communicating your results clearly to business owners in concise, non-technical language. Key job responsibilities What you will do - Work with a product managers, scientists and engineers to define and build business problems. - Research, develop, and deliver machine learning & LLM based solutions in close partnership with end users, other science and engineering teams, and business stakeholders. - Use AWS services like SageMaker and Bedrock to deploy scalable ML models in the cloud. About the team About AWS Diverse Experiences AWS values diverse experiences. Even if you do not meet all of the preferred qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying. Why AWS? Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that’s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses. Inclusive Team Culture Here at AWS, it’s in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences, inspire us to never stop embracing our uniqueness. Mentorship & Career Growth We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional. Work/Life Balance We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve in the cloud. About Sales, Marketing and Global Services (SMGS) 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. We are open to hiring candidates to work out of one of the following locations: Seattle, WA, USA