Careers

Join us at the forefront of Amazon's sustainability initiatives to work on environmental and social advancements that support Amazon's long-term worldwide sustainability strategy. At Amazon, we're working to be the most customer-centric company on earth. To get there, we need exceptionally talented, bright, and driven people. We are looking for a Senior Research Scientist to join our growing Sustainability team to drive the science behind value chain decarbonization. This role will establish Amazon's scientific methodologies for sector- and cross-sectoral decarbonization mechanisms, and establish benchmarks for automated validation and risk assessment. As a Senior Research Scientist, you will be responsible for independently leading assessments of environmental issues across the full spectrum of Amazon businesses and evaluating sustainability impacts across the value chain. You will independently develop quality frameworks and methodologies that enable Amazon to scale procurement of high-quality environmental interventions while maintaining scientific rigor and environmental integrity. Key job responsibilities - Develop quality assessment frameworks for complex environmental interventions, baseline-setting approaches, and measurement methodologies - Build quantitative benchmark and statistical models that enable scalable evaluation across heterogeneous data sources - Create attribution methodologies for supply chain interventions across Amazon's diverse footprint - Develop social and environmental safeguard criteria that integrate community impact assessments - Collaborate with cross-functional teams including procurement, sustainability operations, and business units to translate scientific methodologies into operational requirements - Work under the direction of senior business leaders while acting as lead Subject Matter Expert for value chain decarbonization science, including designing and leading research, data collection, modeling, documentation, interpretation, and validation About the team Diverse Experiences: World Wide Sustainability values diverse experiences. Even if you do not meet all of the qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying. Inclusive Team Culture: It’s in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (inclusive 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.

MULTIPLE POSITIONS AVAILABLE Employer: AMAZON WEB SERVICES, INC. Offered Position: Manager III, Data Science Job Location: Seattle, Washington Job Number: AMZ9749732 Position Responsibilities: Oversee a team of data scientists and business analysts working to build largescale, distributed systems to increase effectiveness of Amazon’s abuse detection systems. Define key business goals. Aggregate data from multiple sources to inform decision making. Manage and quantify improvement in customer experience resulting from research outcomes. Develop and manage a long-term research vision and portfolio of research initiatives, with algorithms and models that have been successfully integrated into production systems. Mentor junior scientists. 40 hours / week, 8:00am-5:00pm, Salary Range $196,914/year to $236,900/year. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, visit: https://www.aboutamazon.com/workplace/employee-benefits. Amazon.com is an Equal Opportunity-Affirmative Action Employer – Minority / Female / Disability / Veteran / Gender Identity / Sexual Orientation.#0000

The Principal Applied Scientist will own the science mission for building next-generation proactive and autonomous agentic experiences across Alexa AI's Personalization, Autonomy and Proactive Intelligence organization. You will technically lead a team of applied scientists to harness state-of-the-art technologies in machine learning, natural language processing, LLM training and application, and agentic AI systems to advance the scientific frontiers of autonomous intelligence and proactive user assistance. The right candidate will be an inventor at heart, provide deep scientific leadership, establish compelling technical direction and vision, and drive ambitious research initiatives that push the boundaries of what's possible with AI agents. You will need to be adept at identifying promising research directions in agentic AI, developing novel autonomous agent solutions, and translating advanced AI research into production-ready agentic systems. You will need to be adept at influencing and collaborating with partner teams, launching AI-powered autonomous agents into production, and building team mechanisms that will foster innovation and execution in the rapidly evolving field of agentic AI. This role represents a unique opportunity to tackle fundamental challenges in how Alexa proactively understands user needs, autonomously takes actions on behalf of users, and delivers intelligent assistance through state-of-the-art agentic AI technologies. As a science leader in Alexa AI, you will shape the technical strategy for making Alexa a truly proactive and autonomous agent that anticipates user needs, takes intelligent actions, and provides seamless assistance without explicit prompting. Your team will be at the forefront of solving complex problems in agentic reasoning, multi-step task planning, autonomous decision-making, proactive intelligence, and context-aware action execution that will fundamentally transform how users interact with Alexa as an intelligent agent. The successful candidate will bring deep technical expertise in machine learning, natural language processing, and agentic AI systems, along with the leadership ability to guide talented scientists in pursuing ambitious research that advances the state of the art in autonomous agents, proactive intelligence, and AI-driven personalization. Experience with multi-agent systems, reinforcement learning, goal-oriented dialogue systems, and production-scale agentic architectures is highly valued. You will lead the development of breakthrough capabilities that enable Alexa to: 1) proactively anticipate user needs through advanced predictive modeling and contextual understanding; 2) autonomously execute complex multi-step tasks with minimal user intervention; 3) reason and plan intelligently across diverse user goals and environmental contexts; 4) learn and adapt continuously from user interactions to improve agentic behaviors; 5) coordinate actions seamlessly across multiple domains and services as a unified intelligent agent. This is a unique opportunity to define the future of conversational AI agents and build technology that will impact hundreds of millions of customers worldwide. Key job responsibilities Technical Leadership - Lead complex research and development projects - Partner closely with the T&C Product and Engineering leaders on the technical strategy and roadmap - Evaluate emerging technologies and methodologies - Make high-level architectural decisions Technical leadership and mentoring: - Mentor and develop technical talent - Set team project goals and metrics - Help with resource allocation and project prioritization from technical side Research & Development - Drive innovation in applied science areas - Translate research into practical business solutions - Author technical papers and patents - Collaborate with academic and industry partners About the team PAPI (Personalization Autonomy and Proactive Intelligence) aims to accelerate personalized and intuitive experiences across Amazon's customer touchpoints through automated, scalable, self-serve AI systems. We leverage customer, device, and ambient signals to deliver conversational, visual, and proactive experiences that delight customers, increase engagement, reduce defects, and enable natural interactions across Amazon touch points including Alexa, FireTV, and Mobile etc. Our systems offer personalized suggestions, comprehend customer inputs, learn from interactions, and propose appropriate actions to serve millions of customers globally.

AWS is one of Amazon’s largest and fastest growing businesses, serving millions of customers in more than 190 countries. We use cloud computing to reshape the way global enterprises use information technology. We are looking for entrepreneurial, analytical, creative, flexible leaders to help us redefine the information technology industry. If you want to join a fast-paced, innovative team that is making history, this is the place for you. AWS Central Economics & Science (ACES) drives best practices for objectively applying economics and science in decision making across AWS. The team collaborates with AWS science and business teams to identify, frame, and analyze complex and ambiguous problems of the highest priority. Through data-driven insights and modeling, ACES supports strategic decision-making across the AWS global organization, including sales operations and business performance optimization. The ACES Sales Channels team is hiring an Applied Scientist (Senior or below) to advance our mission of providing rigorous, causal-inference-driven recommendations for AWS sales optimization. This role will focus on building ML systems with a causal modeling foundation, designing seller incentive mechanisms, and developing intervention strategies across the entire sales motion. Key job responsibilities • Causal ML System Development: Build and deploy machine learning models that emphasize causal inference, ensuring recommendations are grounded in valid interventions • Incentive Design: Define and model incentives that drive desirable behaviors across AWS sales channels, partner programs, and reseller ecosystems • Stakeholder Collaboration: Work with business stakeholders to understand requirements, validate approaches, and ensure practical applicability of scientific solutions • Scientific Rigor: Promote findings at internal conferences and contribute to the team's reputation for methodological excellence A day in the life The ACES Sales Channels team works on understanding and optimizing AWS's sales channels, both direct (generalist and specialist sellers) and indirect (partners and Marketplace). Our work falls into three core areas: developing rigorous causal measurement and modeling frameworks using cutting-edge economics and statistical methods; designing programs and incentives to improve customer and business outcomes; and building ML-based recommendation systems for sellers, partners, and other AWS stakeholders. 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. 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. Hybrid Work We value innovation and recognize this sometimes requires uninterrupted time to focus on a build. We also value in-person collaboration and time spent face-to-face. Our team affords employees options to work in the office every day or in a flexible, hybrid work model near one of our U.S. Amazon offices.

The PXT (People Experience and Technology) AMX Research is seeking a highly skilled and motivated Senior Research Scientist to join our team. You will be leading manager experience research space to support the PXT talent evaluation/talent management initiatives. If you enjoy innovating, thinking big and want to contribute directly to the success of a growing team, you may be a prime candidate for this position. Key job responsibilities Design experiments, test hypotheses, and build actionable models Conduct quantitative analyses of talent management data and trends Conduct qualitative data collection and analysis Partner closely and drive effective collaborations across multi-disciplinary research and product teams Consult on appropriate analytic methodologies and scope research requests

Are you passionate about solving complex business problems at scale through Generative AI? Do you want to build intelligent systems that reason, act, and learn from minimal supervision? Are you excited about taking innovative AI solutions from proof-of-concept to production? If so, we have an exciting opportunity for you 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. We give customers 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. As an Applied Scientist, you will lead the development of next Gen AI solutions to automate complex manual investigation processes at Amazon scale. You will work on some of the most fascinating challenges in applied AI—building systems that reason and act autonomously, learn rich representations from structured and relational data without extensive labels, adapt rapidly from limited examples, improve through feedback and interaction, seamlessly connect visual and textual understanding, and compress complex model capabilities into efficient, deployable systems. Your innovations will deliver significant impact to cost-of-serving customers while maintaining the highest standards of trust and safety. This role offers end-to-end ownership—from initial research and proof-of-concept through production deployment. You will see your innovations serving hundreds of millions of customers within months, not years. Key job responsibilities • Design and build expertise agentic AI systems with multi-step reasoning, autonomous task execution, and multimodal intelligence with capabilities to handle feedback with memory mechanisms. • Productionize large scale models built on top of SFT (Supervised Finetuning) and RFT (Reinforced fine tuning) approaches, few shot approaches based on multimodal datasets • Build novel production ready Deep and conventional ML solutions to aid the multiple potential automation requirements • Identify customer and business problems at project level; invent or extend state-of-the-art approaches for complex workflows involving unstructured text, documents, images, and relational data • Author or co-author research papers for peer-reviewed venues; serve as PC member at conferences when aligned with business needs • Prototype rapidly, iterate based on feedback, and deliver components at SDE I+ level that integrate directly into production-scale systems • Engineer efficient systems balancing model capability, deployment cost, and resource usage; write significant code demonstrating technical excellence and maintainability • Scrutinize algorithm and software performance for improvements; resolve root causes leaving systems more maintainable • Contribute to tactical and strategic planning—team goals, priorities, and roadmaps—while providing architectural guidance for AI systems • Participate in engineering best practices with rigorous peer reviews; communicate design decisions clearly and participate in science reviews • Train new teammates on component construction and integration; mentor less experienced scientists and participate in hiring processes 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.

Innovators wanted! Are you an entrepreneur? A builder? A dreamer? This role is part of an Amazon Special Projects team that takes the company’s Think Big leadership principle to the next level. We focus on creating entirely new products and services with a goal of positively impacting the lives of our customers. No industries or subject areas are out of bounds. If you’re interested in innovating at scale to address big challenges in the world, this is the team for you. As a Research Scientist, you will work with a unique and gifted team developing exciting products for consumers and collaborate with cross-functional teams. Our team rewards intellectual curiosity while maintaining a laser-focus in bringing products to market. Competitive candidates are responsive, flexible, and able to succeed within an open, collaborative, entrepreneurial, startup-like environment. At the intersection of both academic and applied research in this product area, you have the opportunity to work together with some of the most talented scientists, engineers, and product managers. Here at Amazon, we embrace our differences. We are committed to furthering our culture of inclusion. We have thirteen employee-led affinity groups, reaching 40,000 employees in over 190 chapters globally. We are constantly learning through programs that are local, regional, and global. Amazon’s culture of inclusion is reinforced within our 16 Leadership Principles, which remind team members to seek diverse perspectives, learn and be curious, and earn trust. Our team highly values work-life balance, mentorship and career growth. We believe striking the right balance between your personal and professional life is critical to life-long happiness and fulfillment. We care about your career growth and strive to assign projects and offer training that will challenge you to become your best.

Amazon has co-founded and signed The Climate Pledge, a commitment to reach net zero carbon by 2040. As a team, we leverage GenAI, sensors, smart home devices, cloud services, material science, and Alexa to build products that have a meaningful impact for customers and the climate. In alignment with this bold corporate goal, the Amazon Devices & Services organization is looking for a passionate, talented, and inventive Senior Applied Scientist to help build revolutionary products with potential for major societal impact. Great candidates for this position will have expertise in the areas of agentic AI applications, deep learning, time series analysis, LLMs, and multimodal systems. This includes experience designing autonomous AI agents that can reason, plan, and execute multi-step tasks, building tool-augmented LLM systems with access to external APIs and data sources, implementing multi-agent orchestration, and developing RAG architectures that combine LLMs with domain-specific knowledge bases. You will strive for simplicity and creativity, demonstrating high judgment backed by statistical proof. Key job responsibilities As a Senior Applied Scientist on the Energy Science team, you'll design and deploy agentic AI systems that autonomously analyze data, plan solutions, and execute recommendations. You'll build multi-agent architectures where specialized AI agents coordinate to solve complex optimization problems, and develop tool-augmented LLM applications that integrate with external data sources and APIs to deliver context-aware insights. Your work involves creating multimodal AI systems that synthesize diverse data streams, while implementing RAG pipelines that ground large language models in domain-specific knowledge bases. You'll apply advanced machine learning and deep learning techniques to time series analysis, forecasting, and pattern recognition. Beyond technical innovation, you'll drive end-to-end product development from research through production deployment, collaborating with cross-functional teams to translate AI capabilities into customer experiences. You'll establish rigorous experimentation frameworks to validate model performance and measure business impact, building AI-driven products with potential for major societal impact.

Are you ready to be at the forefront of Agentic AI innovation and redefine the future of communication? Join our dynamic Alexa Connections team as a Sr. Applied Scientist, and lead futuristic initiatives that will shape the next generation of intelligent, conversational experiences. In this role, you'll work at the intersection of disruptive AI technologies and real-world impact, making a difference for millions of customers. You'll collaborate with a team of passionate professionals who are as excited about innovation as you are, and together, you'll push the boundaries of what's possible with Alexa+. As a Sr. Applied Scientist, you'll drive the development of novel algorithms and modeling techniques to advance the state of the art with LLMs and real-time Agentic AI solutions that power our next-generation communication features. You'll work closely with cross-functional teams, including product management, engineering, design, and data, to design and deliver innovative solutions that leverage these AI technologies to enable seamless, intelligent communication experiences. You'll also lead the integration of these advanced AI systems into Alexa's core capabilities, ensuring a seamless and intuitive user experience. Key job responsibilities - Develop new inference and training techniques to improve the performance of Large Language Models for Smart Home control and Automation - Develop robust techniques for synthetic data generation for training large models and maintaining model generalization - Research, experiment and build Proof Of Concepts advancing the state of the art in AI & ML for GenAI. - Collaborate with cross-functional teams to architect and execute technically rigorous AI projects. - Thrive in dynamic environment, adapting quickly to evolving technical requirements and deadlines. - Engage in effective technical communication (written & spoken) with coordination across teams. - Conduct thorough documentation of algorithms, methodologies, and findings for transparency and reproducibility. - Publish research papers in internal and external venues of repute - Support on-call activities for critical issues - Mentoring junior scientists to improve their skills, knowledge, and their ability to get things done About the team Alexa Connections aspires to make Alexa+ the world’s most trusted connection assistant for getting things done and creating moments of joy. Our vision emphasizes a) Trust as our foundation for becoming a daily habit, knowing our customers have plentiful choices, b) Completion of end-to-end customer journeys, beyond shipping features, and c) Joy through personalized, proactive experiences, that create a memory.

Amazon Quick Suite is an enterprise AI platform that transforms how organizations work with their data and knowledge. Combining generative AI-powered search, deep research capabilities, intelligent agents and automations, and comprehensive business intelligence, Quick Suite serves tens of thousands of users. Our platform processes thousands of queries monthly, helping teams make faster, data-driven decisions while maintaining enterprise-grade security and governance. From natural language interactions with complex datasets to automated workflows and custom AI agents, Quick Suite is redefining workplace productivity at unprecedented scale. We are seeking a Data Scientist II to join our Quick Data team, focusing on evaluation and benchmarking data development for Quick Suite features, with particular emphasis on Research and other generative AI capabilities. Our mission is to engineer high-quality datasets that are essential to the success of Amazon Quick Suite. From human evaluations and Responsible AI safeguards to Retrieval-Augmented Generation and beyond, our work ensures that Generative AI is enterprise-ready, safe, and effective for users at scale. As part of our diverse team—including data scientists, engineers, language engineers, linguists, and program managers—you will collaborate closely with science, engineering, and product teams. We are driven by customer obsession and a commitment to excellence. Key job responsibilities In this role, you will leverage data-centric AI principles to assess the impact of data on model performance and the broader machine learning pipeline. You will apply Generative AI techniques to evaluate how well our data represents human language and conduct experiments to measure downstream interactions. Specific responsibilities include: * Design and develop comprehensive evaluation and benchmarking datasets for Quick Suite AI-powered features * Leverage LLMs for synthetic data corpora generation; data evaluation and quality assessment using LLM-as-a-judge settings * Create ground truth datasets with high-quality question-answer pairs across diverse domains and use cases * Lead human annotation initiatives and model evaluation audits to ensure data quality and relevance * Develop and refine annotation guidelines and quality frameworks for evaluation tasks * Conduct statistical analysis to measure model performance, identify failure patterns, and guide improvement strategies * Collaborate with ML scientists and engineers to translate evaluation insights into actionable product improvements * Build scalable data pipelines and tools to support continuous evaluation and benchmarking efforts * Contribute to Responsible AI initiatives by developing safety and fairness evaluation datasets 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. 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. Hybrid Work We value innovation and recognize this sometimes requires uninterrupted time to focus on a build. We also value in-person collaboration and time spent face-to-face. Our team affords employees options to work in the office every day or in a flexible, hybrid work model near one of our U.S. Amazon offices.