Careers

The Artificial General Intelligence (AGI) team is looking for a passionate, talented, and inventive Senior Applied Scientist with a strong deep learning background, to build industry-leading technology with Large Language Models (LLMs) and multimodal systems. Key job responsibilities As a Senior Applied Scientist with the AGI team, you will work with talented peers to lead the development of novel algorithms and modeling techniques, to advance the state of the art with LLMs. Your work will directly impact our customers in the form of products and services that make use of speech and language technology. You will leverage Amazon’s heterogeneous data sources and large-scale computing resources to accelerate advances in generative artificial intelligence (GenAI). About the team The AGI team has a mission to push the envelope in LLMs and multimodal systems, in order to provide the best-possible experience for our customers.

Are you inspired by invention? Do you like the idea of seeing how your work impacts the bigger picture? Answer yes to any of these and you’ll fit right in here at Amazon Last Mile Solutions Engineering team. WW AMZL Solutions Engineering team is looking to build out our Simulation team to drive innovation across our Last Mile network. We start with the customer and work backwards in everything we do. If you’re interested in joining a rapidly growing team working to build a unique, solutions advisory group with a relentless focus on the customer, you’ve come to the right place. This is a blue-sky role that gives you a chance to roll up your sleeves and dive into big data sets in order to build simulations and experimentation systems at scale, build optimization algorithms and leverage cutting-edge technologies across Amazon. This is an opportunity to think big about how to solve a challenging problem for the customers. As a Simulation Scientist, you are an analytical problem solver who enjoys diving into data from various businesses, is excited about investigations and algorithms, can multi-task, and can credibly interface between scientists, engineers and business stakeholders. Your expertise in synthesizing and communicating insights and recommendations to audiences of varying levels of technical sophistication will enable you to answer specific business questions and innovate for the future. As a simulation scientist, you will apply cutting edge designs and methodologies for complex use cases across Last Mile network to drive innovation. In addition, you will contribute to the end state vision for simulation and experimentation of future delivery stations at Amazon. Key job responsibilities • Design, develop, and simulate engineering solutions for complex material handling challenges considering human/equipment interactions for the Last Mile network • Lead and coordinate simulation efforts for optimal solutions through equipment specification, material flow, process design, ergonomics, associate experience, operational considerations and site layout • The candidate must have the ability to work with diverse customer groups to solve business problems and provide data solutions that are organized and simple to understand. • Working with technical and non-technical customers to design experiments, simulations, and communicate results • Develop, document and update simulation standards, including standard results reports • Create basic to highly advanced models and run "what-if" scenarios to help drive to optimal solutions • Work closely with internal teams to ensure that every detail is thought through and documented using Standard Operating Procedures and/or structured change control • Work closely with vendors, suppliers and other cross functional teams to come up with innovative solutions • Simultaneously manage multiple projects and tasks while effectively influencing, negotiating, and communicating with internal and external business partners • Conduct post-mortem on simulations, after implementation of new designs, in partnering with Safety and Operations 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!

Take Earth's most customer-centric company. Mix in hundreds of millions of shoppers spending tens of billions of dollars annually, an exciting opportunity to build next-generation shopping experiences, Amazon’s tremendous computational resources, and our extensive e-Commerce experience. What do you get? The most exciting position in the industry. Our team is part of Amazon’s Personalization organization, a high-performing group that leverages Amazon’s expertise in machine learning, big data, distributed systems, and user experience design to deliver the best shopping experiences for our customers. Our team operates at the intersection of search-based recommendations and customer preferences, working on novel ideas to positively impact millions of Amazon customers. Amazon’s internal surveys regularly recognize us as one of the best organizations to work for in the company, with visible high-impact work, low operational load, respectful work-life balance, and continual opportunity to learn and grow. Key job responsibilities - Use machine learning and analytical techniques to create scalable solutions for business problems - Analyze and extract relevant information from large amounts of Amazon's historical business data to help automate and optimize key processes - Design, develop and evaluate highly innovative models for predictive learning - Work closely with software engineering teams to drive model implementations and new feature creations - Establish scalable, efficient, automated processes for large scale data analysis, model development, model validation and model implementation - Research and implement novel machine learning and statistical approaches - Mentor junior scientists; review their work and provide feedback About the team Our mission is to delight every Amazon customer with a personalized shopping experience. We achieve our mission through investments in large scale machine learning, distributed systems and user experience with the purpose of delivering the future of shopping on Amazon. We are seeking a Senior Applied Scientist to build personalized search-based recommendations and evaluate the quality of our personalized recommendation in Amazon-wide scale. Please visit https://www.amazon.science for more information.

The JP Economics team is a central science team working across a variety of topics in the JP Retail business and beyond. We work closely with JP business leaders to drive change at Amazon. We focus on solving long-term, ambiguous and challenging problems, while providing advisory support to help solve short-term business pain points. Key topics include pricing, product selection, delivery speed, profitability, and customer experience. We tackle these issues by building novel economic/econometric models, machine learning systems, and high-impact experiments which we integrate into business, financial, and system-level decision making. Our work is highly collaborative and we regularly partner with JP- EU- and US-based interdisciplinary teams. In this role, you will build production-grade machine learning models to serve best-in-class shopping and delivery experience to millions of customers on Amazon. This requires you to formulate ambiguous business problems into solvable scientific problems, work with large-scale data pipelines, perform extensive data cleaning and exploration, train and evaluate your models in a robust manner, design and conduct live experiments to validate model performance, and automate model inference on AWS infrastructure. The ideal candidate is an experienced data scientist or machine learning engineer who has built machine learning systems in production that delivers business impact at scale in a B2C industry. You are a self-starter who enjoys ambiguity in a fast-paced and ever-changing environment. You are extremely proficient in Python, SQL and distributed computing frameworks. You have excellent understanding of how machine learning models work under the hood. In addition, you may have worked with AWS infrastructure and causal uplift modeling techniques. You think big on the next game-changing opportunity but also dive deep into every detail that matters. You insist on the highest standards and are consistent in delivering results. We are open to consider high-potential candidates with less experiences for a more junior position. Key job responsibilities - Work with Product, Finance and Engineering to formulate business problems into scientific ones - Build large-scale data pipelines for training and evaluating the models using PySpark/SparkSQL - Extensively clean and explore the datasets - Train and evaluate ML models in a robust manner - Design and conduct live experiments to validate model performance - Automate model inference and monitoring and on AWS infrastructure

Are you excited about cutting edge generative AI and LLMs? Are you looking for opportunities to build and deploy them to solve real problems at truly vast scale? At Amazon Fulfillment Technologies AI, we are on a mission to build solutions that perceive, understand, and act to further improve our world-class customer and associate experience - at Amazon scale. We are looking for an Applied Scientist who will help us build next level systems to improve the safety of our warehouses with the help of generative AI and LLMs. Together, we will be pushing the state of the art of one of the most complex systems in the world: Amazon's Fulfillment Network. Key job responsibilities In this role, you will dive deep into our fulfillment network, understand complex processes and channel your insights to build large scale deep learning and GenAI models (LLMs) that will be able to understand the state of our buildings and work with our warehouse teams to help identify and mitigate safety risks. You will face a high level of research ambiguity and problems that require creative, ambitious, and inventive solutions. You will work with and in a team of applied scientists to solve cutting edge problems going beyond the published state of the art that will drive transformative change on a truly global scale. A day in the life 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 Amazon Fulfillment Technologies (AFT) powers Amazon’s global fulfillment network. We invent and deliver software, hardware, and data science solutions that orchestrate processes, robots, machines, and people. We harmonize the physical and virtual world so Amazon customers can get what they want, when they want it. The AFT AI team has deep expertise developing cutting edge AI solutions at scale and successfully applying them to business problems in the Amazon Fulfillment Network. These solutions typically utilize machine learning and computer vision techniques, applied to text, sequences of events, images or video from existing or new hardware. We influence each stage of innovation from inception to deployment, developing a research plan, creating and testing prototype solutions, and shepherding the production versions to launch.

About Amazon Advertising: Amazon Advertising operates at the intersection of eCommerce and advertising, offering a rich array of digital display advertising solutions with the goal of helping our customers find and discover anything they want to buy. We help advertisers of all types to reach Amazon customers on Amazon.com, across our other owned and operated sites, on other high quality sites across the web, and on millions of mobile devices. We start with the customer and work backwards in everything we do, including advertising. If you’re interested in joining a rapidly growing team working to build a unique, world-class advertising group with a relentless focus on the customer, you’ve come to the right place. About our team: BOLDx (Brands, OTT, Live Gaming, Display Advertising Experiences) is on a mission to make Amazon the best in class destination for shoppers to discover, engage and build affinity with brands, making shopping beautiful, delightful, and personal. Our team builds the central Brand Understanding foundation for Amazon ads and beyond. We focus on enabling Amazon brand ads businesses to align customers' brand shopping intent and brands' unique value (e.g., intelligent query/shopper-to-brand understanding, brand value/differentiator attribute extraction, and brand profile building). We provide large-scale offline and online Brand Understanding data services, powered by cutting edge Machine Learning technologies (e.g., Large-Language-Model, Multi-Modal Deep Neural Networks, Statistical Modeling). We also enables customer-brand engagement enhancement through intelligent UX and efficient ads serving. About this Role: We are looking for a passionate, talented Senior Applied Scientist in the field of Natural Language Processing (NLP), Computer Vision (CV), Large Language Model (LLM), Ads Recommender Systems, and/or Information Retrieval, to invent and build scalable solutions for a state-of-the-art context-aware Brand Understanding. A successful candidate will have strong machine learning background and a desire to push the boundary of one or more of the above areas. The ideal candidate is expected to leading the effort of building key ML features, contribute to the collaborative and innovative spirit within the team, and bring cutting-edge applied research to raise the bar within the team.

The Fulfillment by Amazon (FBA) team is looking for a passionate, curious, and creative Senior Applied Scientist, with expertise in machine learning (ML) and a proven record of solving business problems through scalable ML solutions, to join our top-notch cross-domain FBA science team. We want to learn seller behavior, understand seller experience, build automated LLM-based solutions to sellers, design seller policies and incentives, and develop science products and services that empower third-party sellers to grow their businesses. We also predict potentially costly defects that may occur during packing, shipping, receiving and storing the inventory. We aim to prevent such defects before occurring while we are also fulfilling customer demand as quickly and efficiently as possible, in addition to managing returns and reimbursements. To do so, we build and innovate science solutions at the intersection of ML, statistics, economics, operations research, and data analytics. As a senior applied scientist, you will propose and deploy solutions that draw from a range of scientific areas such as supervised and unsupervised learning, recommendation systems, statistical learning, LLMs, and reinforcement learning. This role has high visibility to senior Amazon business leaders and involves working with other scientists, and partnering with engineering and product teams to integrate scientific work into production systems. Key job responsibilities As a senior member of the science team, you will - play an integral role in building Amazon's FBA supply chain management system. - Research and develop ML models to solve diverse business problems faced in seller inventory management systems. - Define a long-term science vision and roadmap for the team, driven fundamentally from our customers' needs, translating those directions into specific plans for research. - Drive and execute ML projects/products end-to-end: from ideation, analysis, prototyping, development, metrics, and monitoring. - Review and audit modeling processes and results for other scientists, both junior and senior. - Advocate the right ML solutions to business stakeholders, engineering teams, as well as executive level decision makers. A day in the life In this role, you will be a technical leader in ML with significant scope, impact, and visibility. As a senior scientist on the team, you will be involved in every aspect of the process - from idea generation, business analysis and scientific research, through to development and deployment of advanced models - giving you a real sense of ownership. From day one, you will be working with experienced scientists, engineers, and designers who love what they do. You are expected to make decisions about technology, models, and methodology choices. You will strive for simplicity, and demonstrate judgment backed by mathematical proof. You will also collaborate with the broader decision and research science community in Amazon to broaden the horizon of your work and mentor engineers and scientists. The successful candidate will have strong expertise in applying ML models in an applied environment and is looking for her/his next opportunity to innovate, build, deliver, and impress. We are seeking someone who wants to lead projects that require innovative thinking and deep technical problem-solving skills to create production-ready machine learning solutions. The candidate will need to be entrepreneurial, wear many hats, and work in a fast-paced, high-energy, highly collaborative environment. We value highly technical people who know their subject matter deeply and are willing to learn new areas. We look for individuals who know how to deliver results and show a desire to develop themselves, their colleagues, and their career. About the team Fulfillment by Amazon (FBA) is a service that allows sellers to outsource order fulfillment to Amazon, allowing sellers to leverage Amazon’s world-class facilities to provide customers Prime delivery promise. Sellers gain access to Prime members worldwide, see their sales lift, and are free to focus their time and resources on what they do best while Amazon manages fulfillment. Over the last several years, sellers have enjoyed strong business growth with FBA shipping more than half of all products offered by Amazon. FBA focuses on helping sellers with automating and optimizing the third-party supply chain. FBA sellers leverage Amazon’s expertise in ML, optimization, data analytics, econometrics, and market design to deliver the best inventory management experience to sellers. We work full-stack, from foundational backend systems to future-forward user interfaces. Our culture is centered on rapid prototyping, rigorous experimentation, and data-driven decision-making.

Specialist DataLens (SDL) team builds out persona-based data, reports, and insights focused on Specialization at AWS. Users can determine impact of their contributions, identify customer demand signals, and obtain insights to make business decisions to maximize their impact without having to navigate different dashboards or creating ad-hoc reports. The SDL applied scientist will enhance the present models by designing and leveraging Generative AI capabilities to identify customer trends, provide recommendations for service gaps, simplify data discovery and maximize impact. We are seeking an applied scientist who has a solid background in Machine Learning and Data Science, deep passion for building data-driven solutions, ability to formulate data insights and scientific vision, and has a proven track record of executing complex projects and delivering business impact. Key job responsibilities • Have a deep understanding of the business requirements and reporting metrics to build a data platform implemented with Generative AI/machine learning methodologies to highlight business insights. • Own the end-to-end machine learning lifecycle including identifying hidden relationships between data-variables, feature engineering, machine learning model development, training, validation using Amazon technologies such as Bedrock/Sagemaker. • Design, develop, and train large language models (LLMs) using advanced machine learning techniques and prompt engineering. Ensure models are optimized for performance, accuracy, and efficiency in various applications. •Evaluate model performance using appropriate metrics and benchmarks. Conduct thorough testing and validation to ensure robustness, reliability, and fairness of the LLMs. • Collaborate with business intelligence engineers, technical program management, product management, software developers, data engineering, ML/AI specialist teams and business leaders to provide science support. Communicating feedback; develop, test and deploy a wide range of statistical, econometric, and machine learning models. • Implement, train and validate generative AI application execution within BI dashboards. • Communicate verbally and in writing to business customers with various levels of technical knowledge. • Stay up-to-date with the latest advancements in GenAI/machine learning and apply them to drive continuous improvement in our data platform. About the team The Specialist DataLens team is part of the AWS Specialist Technology team, which is focused on empowering specialists to create customer outcomes, accelerate specialist knowledge, and scaling specialist productivity to the field. The datalens team provides the mechanisms to understand where to invest in specialization. The datalens team is part of the team building out Specialist mechanisms via hands-on workshops, technical communities, solutions and more. 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. Utility Computing (UC) 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. 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. 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. 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. 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.

The Applied Scientist in NLP within Customer Engagement Tech, Self-Service and Automation team will work on the research, design, and implementation of solutions to key challenges in developing conversational AI systems based on large pretrained language models, that can understand and communicate with customers in a natural and contextually appropriate manner. This involves tackling complex problems in areas such as multi-turn dialogue management, knowledge grounding, and open-ended generation and assessment of dialogue quality and style of the conversational model. Key job responsibilities Key job responsibilities 1. Lead the research and development of LLM-based chatbots and conversational AI systems for customer service applications. 2. Design and implement state-of-the-art NLP and ML models for tasks such as language understanding, dialogue management, and response generation and dialogue quality assessment. 3. Collaborate with cross-functional teams, including data scientists, software engineers, and product managers, to integrate LLM-based solutions into Amazon's customer service platforms. 4. Develop and implement strategies for data collection, annotation, and model training to ensure high-quality and robust performance of the chatbots. 5. Conduct experiments and evaluations to measure the performance of the developed models and systems, and identify areas for improvement. 6. Stay up-to-date with the latest advancements in NLP, LLMs, and conversational AI, and explore opportunities to incorporate new techniques and technologies into Amazon's customer service solutions. 7. Collaborate with internal and external research communities, participate in conferences and publications, and contribute to the advancement of the field. A day in the life We thrive on solving challenging problems to innovate for our customers. By pushing the boundaries of technology, we create unparalleled experiences that enable us to rapidly adapt in a dynamic environment. Our decisions are guided by data, and we collaborate with engineering, science, and product teams to foster an innovative learning environment 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! Benefits Summary: 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 About the team Join our team of scientists and engineers who develop and deploy LLM-based Conversational AI systems to enhance Amazon's customer service experience and effectiveness. We work on innovative solutions that help customers solve their issues and get their questions answered efficiently, and associate-facing products that support our customer service associate workforce.

This is an exciting opportunity to shape the future of AI and make a real impact on our customers' generative AI journeys. Join the Generative AI Innovation Center to help customers shape the future of Responsible Generative AI while prioritizing security, privacy, and ethical AI practices. In this role, you will play a pivotal role in guiding AWS customers on the responsible and secure adoption of Generative AI, with a focus on Amazon Bedrock, our fully managed service for building generative AI applications. AWS Generative AI Innovation Center is looking for a Generative AI Data Scientist, who will guide customers on operationalizing Generative AI workloads with appropriate guardrails and responsible AI best practices, including techniques for mitigating bias, ensuring fairness, vulnerability assessments, red teaming, model evaluations, hallucinations, grounding model responses, and maintaining transparency in generative AI models. You'll evangelize Responsible AI (RAI), help customers shape RAI policies, develop technical assets to support RAI policies including demonstrating guardrails for content filtering, redacting sensitive data, blocking inappropriate topics, and implementing customer-specific AI safety policies. The assets you develop, will equip AWS teams, partners, and customers to responsibly operationalize generative AI, from PoCs to production workloads. You will engage with policy makers, customers, AWS product owners to influence product direction and help our customers tap into new markets by utilizing GenAI along with AWS Services. As part of the Generative AI Worldwide Specialist organization, Innovation Center, you will interact with AI/ML scientists and engineers, develop white papers, blogs, reference implementations, and presentations to enable customers and partners to fully leverage Generative AI services on Amazon Web Services. You may also create enablement materials for the broader technical field population, to help them understand RAI and how to integrate AWS services into customer architectures. You must have deep understanding of Generative AI models, including their strengths, limitations, and potential risks. You should have expertise in Responsible AI practices, such as bias mitigation, fairness evaluation, and ethical AI principles. In addition you should have hands on experience with AI security best practices, including vulnerability assessments, red teaming, and fine grained data access controls. Candidates must have great communication skills and be very technical, with the ability to impress Amazon Web Services customers at any level, from executive to developer. Previous experience with Amazon Web Services is desired but not required, provided you have experience building large scale solutions. You will get the opportunity to work directly with senior ML engineers and Data Scientists at customers, partners and Amazon Web Services service teams, influencing their roadmaps and driving innovation. Travel up to 40% may be possible. 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 - Guide customers on Responsible AI and Generative AI Security: Act as a trusted advisor to our customers, helping them navigate the complex world of Generative AI and ensure they are using it responsibly and securely. - Operationalize generative AI workloads: Support customers in taking their generative AI projects from proof-of-concept to production, implementing appropriate guardrails and best practices. - Demonstrate Generative AI Risks and Mitigations: Develop technical assets and content to educate customers on the risks of generative AI, including bias, offensive content, cyber threats, prompt hacking, and hallucinations. - Collaborate with GenAI Product/Engineering and Customer-Facing Builder Teams: Work closely with the Amazon Bedrock product and engineering teams and customer-facing builders to launch new services, support beta customers, and develop technical assets. - Thought Leadership and External Representation: Serve as a thought leader in the Generative AI space, representing AWS at industry events and conferences, such as AWS re:Invent. - Develop technical content, workshops, and thought leadership to enable the broader technical community, including Solution Architects, Data Scientists, and Technical Field Community members. About the team About the team 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 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 in the cloud.