Careers

Join us in a historic endeavor to make Multimodal AI accessible to the world with breakthrough research! The Multimodal AI team has a world-leading team of researchers and academics. We develop the algorithms and models that power AWS AI services such as Bedrock Data Automation, Transcribe, Textract and Rekognition. We are looking for Principal Scientists to join us and make the AI revolution happen through innovative research inspired by customer needs. A Principal Scientist in AWS AI Labs is a hands-on contributor, who identifies and shapes directions for forward-looking research and develop innovative solutions to hard, previously unsolved customer problems. You will partner with senior managers and Directors and guide the research of individual scientists. You will work closely with engineering teams to define the architectures and solutions that transform multimodal AI research in to services operating at AWS scale. You are expected to lead new areas of research and publish your research results at peer reviewed conferences and workshops. AWS, the world-leading provider of cloud services, has fostered the creation and growth of countless new businesses, and is a positive force for good. Our customers bring problems which will give scientists endless opportunities to see their research have a positive and immediate impact in the world. You will have the opportunity to partner with technology and business teams to solve real-world problems, have access to virtually endless data and computational resources, and to world-class engineers and developers that can help bring your ideas into the world. Our research themes include, but are not limited to: multimodal understanding of documents/video/audio, post-training of multimodal FMs including supervised fine tuning and RL, automated annotations, in-context learning and context compression, model distillation and optimization. We are currently located in the US (Seattle and Bay Area) and Israel (Haifa and Tel Aviv). Additional locations include New York City. About the team About Us Inclusive Team Culture Here at AWS, we embrace our differences. We are committed to furthering our culture of inclusion. We have ten employee-led affinity groups, reaching 40,000 employees in over 190 chapters globally. We have innovative benefit offerings, and host annual and ongoing learning experiences. Amazon’s culture of inclusion is reinforced within our 14 Leadership Principles, which remind team members to seek diverse perspectives, learn and be curious, and earn trust. Work/Life Balance Our team puts a high value on work-life balance. It isn’t about how many hours you spend at home or at work; it’s about the flow you establish that brings energy to both parts of your life. We believe striking the right balance between your personal and professional life is critical to life-long happiness and fulfillment. We offer flexibility in working hours and encourage you to find your own balance between your work and personal lives. Mentorship & Career Growth Our team is dedicated to supporting new members. We have a broad mix of experience levels and tenures, and we’re building an environment that celebrates knowledge sharing and mentorship. Our senior members enjoy one-on-one mentoring and thorough, but kind, code reviews. We care about your career growth and strive to assign projects based on what will help each team member develop into a better-rounded engineer and enable them to take on more complex tasks in the future.

Are you excited about solving complex business problems at scale through GenAI? Are you fascinated about the application of Agentic AI and LLMs on real-life scenarios? Are you looking to invent solutions that drive Autonomous Artificial Intelligence? If so, we are looking for you to fill a challenging position on Amazon's Trustworthy Shopping Experience (TSE) team. At TSE, our vision is to guarantee customers a worry-free shopping experience by earning their trust that the products they buy are safe, authentic, and compliant with regulations and policy, and giving them the confidence that Amazon stands behind every product and will make it right in the rare chance anything goes wrong. We do this in close partnership with our selling partners and empower them with best-in-class tools and expertise required to offer a high-quality selection of compliant products that customers trust. When we do this consistently, we help selling partners grow their business and power their long-term success. As an Applied Scientist on the team, you will be responsible for delivering the science solutions required to automate complex manual investigation processes, especially by leveraging LLMs. You will handle Amazon scale use-cases with significant impact to the cost of serving Customers. Key job responsibilities - You invent and design new solutions for scientifically-complex problem areas and/or opportunities in existing or new business initiatives. - You design experiments and define the science approach to solve critical business use-cases for automating manual work that involves unstructured text, documents, images, symbols, etc. - Your work focuses on ambiguous problem areas at the product level, where the business problem or opportunity may not yet be crisply defined. - You drive or heavily influence the design of scientifically-complex software solutions or systems, for which you personally write significant parts of the critical scientific novelty. - You provide a system-wide view and design guidance for solutions that can be brand new or evolve from existing ones. - You apply and set the example for best practices in software engineering, and systematically peer review code written by your team members. - You set standards and proactively drive components to use and improve on state-of-the-art techniques. - You autonomously drive thoughtful discussions with customers, engineers, and scientist peers, and build consensus on larger projects and factor complex efforts into independent tasks that can be performed by you and others. About the team Investigation technology Product team in TSE is responsible for the human-in-the-loop products and technology used in the risk investigations at Amazon. The team is also responsible for reducing the cost of performing the investigations, by automating wherever possible and optimizing the experience where manual interventions are needed. The team leverages state-of-the art technology and GenAI to deliver the products and associated goals.

Come be a part of a rapidly expanding $35 billion-dollar global business. At Amazon Business, a fast-growing startup passionate about building solutions, we set out every day to innovate and disrupt the status quo. We stand at the intersection of tech & retail in the B2B space developing innovative purchasing and procurement solutions to help businesses and organizations thrive. At Amazon Business, we strive to be the most recognized and preferred strategic partner for smart business buying. Bring your insight, imagination and a healthy disregard for the impossible. Join us in building and celebrating the value of Amazon Business to buyers and sellers of all sizes and industries. Unlock your career potential. The Analytics Data Product & Tech (ADAPTech) team is a strategic partner to the WW Sales organization, playing a key role in driving sales productivity through three primary workstreams. First, the Analytics team provides data-driven insights and reporting tools to measure business, customer, and employee performance. Second, the Products and Science team develops transformative tools that help Account Executives (AEs) to prioritize accounts, recommend product features, and engage more effectively with customers. Finally, the Data Management and Governance teams ensure AEs have access to accurate and enriched customer information across our tools. We're seeking an Data Scientist to join our team to improve the productivity and efficiency of AEs. You'll be part of expanding GenAI capabilities and scaling its impact across global markets. A successful Data Scientist at Amazon demonstrates bias for action and operates in a startup environment, with leadership skills, and proven ability to build and manage medium-scale modeling projects, identify data requirements, build methodology and tools that are statistically grounded. We need great leaders to think big and design new solutions to solve complex problems using machine learning (ML) and Generative AI techniques to improve our customers’ experience when using AB. You have hands-on experience making the right decisions about technology, models and methodology choices. Key job responsibilities As a Data Scientist, you will primarily leverage machine learning techniques and generative AI to outreach customers based on their life cycle stage, behavioral patterns, and purchase history. You may also perform text mining and insight analysis of real-time customer conversations and make the model learn and recommend the solutions. Your work will directly impact the trust customers place in Amazon Business. You will partner with product management and technical leadership to identify opportunities to innovate customer journey experiences. You will identify new areas of investment and work to align product roadmaps to deliver on these opportunities. As a science leader, you will not only develop unique scientific solutions, but also play a crucial role in shaping strategies. Additional responsibilities include: - Ability to understand a business problem and the available data and identify what statistical or ML techniques can be applied to answer a business question - Design and lead large projects and experiments from beginning to end, and drive solutions to complex or ambiguous problems - Use broad expertise to recommend the right strategies, methodologies, and solve challenges using statistical modeling, machine learning, optimization, and/or other approaches for quantifiable impact on the business - Build models that measure incremental value, predict growth, define and conduct experiments to optimize engagement of AB customers, and communicate insights and recommendations to product, sales, and finance partners. A day in the life In this role, you will be a technical expert with significant scope and impact. You will work with Technical Product Managers, Data Engineers, other Scientists, and Salesforce developers, to build new and enhance existing ML models to optimize customer experience. You will prototype and test new ideas, iterate quickly, and deploy models to production. Also, you will conduct in-depth data analysis and feature engineering to build robust ML models.

Alexa International Tech (AIT) team is looking for a passionate and outcome-driven Applied Science Manager to lead the science team behind some of Alexa’s industry-leading technology. The team is focused on delivering exceptional digital personal assistance (Alexa+ ) experience for international customers using state of the art techniques in Large Language Models (LLMs) and multimodal systems. Key job responsibilities As an Applied Science Manager in AIT you will: * Lead and grow a team of Applied Scientists working to develop and evolve Large Language models powering Alexa+ for international locales and languages * Define and execute on science roadmap for the team, working backwards from customer needs, business priorities and science capabilities * Drive the development of scalable multi-lingual NLP and LLM solutions and develop frameworks to evaluate various aspects of LLM performance * Partner with engineering teams to implement production-ready scientific solutions * Recruit, mentor, and develop top scientific talent * Foster a culture of innovation while maintaining high scientific standards * Review and provide guidance on experimental design, methodology, implementation and continuous improvement of science solutions * Collaborate with product, engineering, and business teams to continuously improve customer experience A day in the life * Review key metrics, goals and project progress from your team * Provide direction and guidance to your team, and unblock or coarse correct as need be, to ensure science solutions are on track and delivered with high quality. * Actively participate and contribute to launch readiness forums, leadership reviews and technical design reviews. * Meet with product managers to align on roadmap priorities and scientific requirements * Provide technical mentorship to team members on their projects * Review and give feedback on scientific documentation and methodology * Collaborate with engineering partners on implementation approaches * Lead team meetings focused on scientific innovation and best practices * Contribute through industry first research to drive the innovation forward. * Engage with the broader Amazon science community to share learnings and stay current with latest developments

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. 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! As a Senior Data Scientist on this team you will: - Lead Data Science solutions from beginning to end. - Deliver with independence on challenging large-scale problems with complexity and ambiguity. - Write code (Python, R, Scala, SQL, etc.) to obtain, manipulate, and analyze data. - Build Machine Learning and statistical models to solve specific business problems. - Retrieve, synthesize, and present critical data in a format that is immediately useful to answering specific questions or improving system performance. - Analyze historical data to identify trends and support optimal decision making. - Apply statistical and machine learning knowledge to specific business problems and data. - Formalize assumptions about how our systems should work, create statistical definitions of outliers, and develop methods to systematically identify outliers. Work out why such examples are outliers and define if any actions needed. - Given anecdotes about anomalies or generate automatic scripts to define anomalies, deep dive to explain why they happen, and identify fixes. - Build decision-making models and propose effective solutions for the business problems you define. - Conduct written and verbal presentations to share insights to audiences of varying levels of technical sophistication. Why you will love this opportunity: Amazon has invested 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

Amazon Advertising is one of Amazon's fastest growing and most profitable 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! As an Applied Scientist on this team, you will: - Be a strong contributor to Machine Learning; lending effort within this team and across other teams. - 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. - Drive end-to-end Machine Learning projects that have a high degree of ambiguity, scale, complexity. - Build 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. - Research new and innovative machine learning approaches. 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

Amazon Advertising is one of Amazon's fastest growing and most profitable 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! As a Senior Applied Scientist on this team, you will: - Be the technical leader in Machine Learning; lead efforts within this team and across other teams. - 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. - Drive end-to-end Machine Learning projects that have a high degree of ambiguity, scale, complexity. - Build 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. - Research new and innovative machine learning approaches. - Recruit Applied Scientists to the team and provide mentorship. 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

Amazon Web Services (AWS) is looking for a Principal Applied Scientist to join the Amazon Q team. Q is AWS’s enterprise generative AI assistant that helps users answer questions, summarize documents, generate content, take actions, and automate workflows using information across enterprise systems. As a key member of this team, you will lead research and development efforts in generative AI and Agentic AI to enable intelligent agents that perform complex reasoning, automate multi-step workflows, and make enterprise users significantly more productive. You’ll work on building and optimizing multi-modal foundation models, training and fine-tuning state-of-the-art LLMs, and architecting systems that scale efficiently across domains. This role blends science leadership, hands-on innovation, and deep collaboration with engineering teams to bring research into production. Key job responsibilities Lead the design and development of foundational models and intelligent agent architectures tailored to enterprise use cases. Partner with engineering, product, and UX teams to integrate generative AI into the Amazon Q assistant. Drive experimentation to improve model accuracy, safety, latency, and cost efficiency. Mentor other scientists and engineers, helping raise the technical bar across the team. Contribute to and publish in top-tier conferences or file patents based on novel research contributions. About the team Amazon Q is a generative AI-powered assistant that helps employees become more productive by answering questions, generating content, summarizing data, and automating workflows using enterprise information. Our team builds the intelligence behind Q, leveraging large language models, retrieval-augmented generation, and agentic architectures to orchestrate complex workflows securely and at scale. We’re focused on building systems that reason, plan, and act across multiple modalities and business tools. As part of AWS’s broader Agentic AI initiative, we’re shaping the future of enterprise AI—empowering organizations to solve problems faster, reduce operational overhead, and unlock new levels of efficiency and decision-making.

The Customer Engagement Technology (CET) team leads AI/LLM- (Large Language Model) driven customer experience transformation using task-oriented dialog systems. We develop multi-modal, multi-turn, goal-oriented dialog systems that can handle customer issues at Amazon scale across multiple languages. These systems are designed to adapt to changing company policies and invoke correct APIs to automate solutions to customer problems. Additionally, we enhance associate productivity through response/action recommendation, summarization to capture conversation context succinctly, retrieving precise information from documents to provide useful information to the agent, and machine translation to facilitate smoother conversations when the customer and agent speak different languages. Key focus areas include: - Task-Oriented Dialog Systems: Building reliable, scalable, and adaptive LLM-based agents for understanding intents, determining eligibilities, making API calls, confirming outcomes, and exploring alternatives across hundreds of customer service intents, while adapting to changing policies. - Lifelong Learning: Researching continuous learning approaches for injecting new domain knowledge while retaining the model's foundational abilities and preventing catastrophic forgetting. - Agentic Systems: Developing a modular agentic framework to handle multi-domain conversations through appropriate system abstractions. - Complex Multi-turn Instruction Following: Identifying approaches to guarantee compliance with instructions that specify standard operating procedures for handling multi-turn complex scenarios. - Inference-Time Adaptability: Researching inference-time scaling methods and improving in-context learning abilities of custom models to enable real-time adaptability to new features, actions, or bug fixes without solely relying on retraining. - Context Adherence: Exploring methods to ground responses in specific customer attributes, account information, and behavioral data to prevent hallucinations and ensure high-fidelity responses. - Policy Grounding: Investigating techniques to align bot behavior with evolving company policies by grounding on complex, unstructured policy documents, ensuring consistent and compliant actions. - End-to-End Dialog Policy Optimization: Researching alignment approaches to optimize successful dialog completions. - Scalable Evaluations: Developing automated approaches to evaluate the quality of experience, and correctness of agentic resolutions. Key job responsibilities - Research and development of LLM-based chatbots and conversational AI systems for customer service applications. - Design and implement state-of-the-art NLP and ML models for tasks such as language understanding, dialogue management, and response generation. - Collaborate with cross-functional teams, including data scientists, software engineers, and product managers, to integrate LLM-based solutions into Amazon's customer service platforms. - Develop and implement strategies for data collection, annotation, and model training to ensure high-quality and robust performance of chatbot systems. - Conduct experiments and evaluations to measure the performance of developed models and systems to identify areas for improvement. - 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. - 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 adapt rapidly 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 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, as well as associate-facing products that support our customer service associate workforce.

Amazon is looking for a passionate, talented, and inventive Applied Scientist with a strong machine learning background to help build industry-leading technology in generative AI and foundational models. As part of our AI team in Amazon AWS, you will work alongside internationally recognized experts to develop novel algorithms and modeling techniques to advance the state-of-the-art in generative AI. Your work will directly impact millions of our customers in the form of products and services that make use of speech, vision and language technology. You will gain hands on experience with Amazon’s heterogeneous speech, text, image and structured data sources, and large-scale computing resources to accelerate advances in machine learning and foundation models. More specifically, you will have the opportunity to impact millions of our customers by researching and building innovative solutions using Agentic AI. Agentic AI drives innovation at the forefront of artificial intelligence, enabling customers to transform their businesses through cutting-edge generative AI solutions. We build and deliver the foundational AI services that power the future of cloud computing, helping organizations harness the potential of AI to solve their most complex challenges. Join our dynamic team of AI/ML practitioners, applied scientists, software engineers, and solution architects who work backwards from customer needs to create groundbreaking technologies. If you're passionate about shaping the future of AI while making a meaningful impact for customers worldwide, we want to hear from you. A day in the life A day in the life 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) 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.