ARA Program Rules

Last updated: March 26, 2025

By applying to or participating in the Amazon Research Awards Program (the “ARA Program”), you (defined below) agree to the following rules (“Rules”). These Rules are solely between Amazon.com, Inc. and its affiliates (“Amazon”, “we”, “us”, or “our”) and the entity that you represent (“you” or “your”), including the lead researcher/s who applies to the ARA Program (the “Principal Investigator”) and any members of the research team. Capitalized terms not defined herein may be defined in the AWS Agreements (as defined below). You and/or the Principal Investigator are responsible for distributing these Rules to all members of the research team before they participate in any research in connection with a proposal funded by the ARA Program.

I. Eligibility Requirements

To be eligible for an ARA Program award (“Award”), the Principal Investigator must be (1) either a full-time faculty member at an accredited academic institution or a permanent researcher at a non-governmental organization with recognized legal status in its country (equivalent to 501(c)(3) status under the United States Internal Revenue Code) and (2) at or above the age of majority in their jurisdiction of residence at the time of application. Each Principal Investigator is permitted to submit only one proposal to the ARA Program per call for proposal period.

By submitting your proposal to the ARA Program, you represent that your Principal Investigator:

(a) is not a paid employee of a government entity (other than an accredited academic institution);

(b) is not under US export controls or sanctions;

(c) has not been a director, officer, employee, intern or contractor of Amazon within the 12 months preceding submission of your proposal to the ARA Program (“Ineligible Personnel”);

(d) is not a member of the immediate family or household of Ineligible Personnel; and

(e) has not participated in or had decision-making authority over any cloud infrastructure procurements involving Amazon.

The ARA Program is void in Cuba, Iran, Syria, North Korea and the Crimea, Luhansk and Donetsk regions of Ukraine, and where otherwise prohibited by law.

Amazon employees, including employees of Amazon Web Services, Inc. (“AWS”), are not eligible to receive an Award.

Amazon is not responsible for your internal organizational policies and procedures that may restrict your (including the Principal Investigator’s) ability to submit a proposal to the ARA Program.

II. Application Content

No proposal to the ARA Program may contain any confidential information and no part may be marked as ‘confidential.’ Amazon does not accept any legal obligation (whether of confidentiality, compensation, return or otherwise) with respect to any proposals. Amazon reserves the right to implement competitive, similar, or identical ideas in the future, without restriction or obligation. You understand and acknowledge that Amazon has wide access to technology, designs, and other materials, and may work on and/or develop projects and ideas that may be competitive with, similar to, or identical to your proposal in theme, idea, format or other respects, inclusive. You acknowledge and agree that you will not be entitled to any compensation as a result of Amazon’s use of any such similar or identical material that has or may come to Amazon from other sources.

You represent and warrant that your proposal:

(a) is either your original work or an update to your original work;

(b) does not, to your knowledge, infringe any third-party patent rights; and

(c) does not, to your knowledge, infringe, misappropriate or otherwise violate any other third-party intellectual property rights (i.e., other than patent rights), including any copyrights, trade secrets, trademarks, contract or licensing rights, rights of publicity or privacy, or moral rights.

III. Awards

Proposals selected for funding will receive an Award that may include cash, Promotional Credit (as defined in the AWS Promotional Credit Terms & Conditions), or both. Award funding is not extendable or transferable without our written consent, but you may submit new proposals for subsequent ARA Program calls.

All Award amounts will be determined by Amazon in its sole discretion. Any cash component of an Award:

(a) will be structured as a one-time unrestricted gift to your Principal Investigator’s academic institution or organization;

(b) will be provided directly to your academic institution or organization for distribution and management; and

(c) may not be used for indirect expenses which are not allocable, reasonable, adequately documented, and consistent with established policies and practices of your academic institution or organization.

You are responsible for the administration and apportionment of any costs and expenses associated with an Award, including any allowable and allocable overhead or indirect costs. In order to process any cash Award, you will be required to complete administrative requirements, which may include submitting a W-9 form to us, completing a tax questionnaire, and registering in Amazon’s Payee Central System. If you do not fulfill the administrative requirements for processing cash Awards within two years of your receipt of an Award notification, Amazon reserves the right to withhold payment. Any payment from Amazon to you under the Award may be issued by a purchase order. Except where prohibited by law, you are responsible for all taxes (including income tax and value added tax) that may be imposed on you by relevant local tax authorities.

These Rules, the agreements referenced herein, and any other agreement regarding the relationship between you and Amazon will constitute a Master Agreement under the terms of the purchase order.

IV. AWS Customer Agreement and AWS Promotional Credit Terms & Conditions

Amazon may make available to you an amount of AWS promotional computing credits (“AWS Credits”) for use in support of this Agreement. AWS Credits provided to University under this Agreement are subject to the AWS Promotional Credit Terms and Conditions (as may be updated from time to time on the AWS website). You acknowledge and agree that any use of AWS services, including but not limited to use of AWS Credits, is subject to the terms and conditions set forth in the AWS Customer Agreement (https://aws.amazon.com/agreement/), and/or any separate, bespoke agreement that you have entered into with Amazon governing use of AWS services (collectively, the “AWS Agreements”). In the event of any conflict between this Agreement and the AWS Agreements, the terms of the AWS Agreements shall take precedence.

V. Privacy

You acknowledge and agree that we may collect, store, share, and otherwise use personally identifiable information provided during the ARA Program application process, including but not limited to, name, mailing address, phone number, and email address. All personally identifiable information collected is subject to, and will be used in accordance with, the Amazon Privacy Notice, including for administering the ARA Program and verifying applicants’ identities, addresses, and telephone numbers in the event a proposal is selected for funding. By participating in the ARA Program, you consent to the transfer of personal data to the United States for purposes of administering the ARA Program, conducting publicity about the ARA Program, and additional purposes that are consistent with goals relating to the ARA Program. The data controller for information collected by us is Amazon.com, Inc., 410 Terry Ave North, Seattle, Washington 98109, USA.

VI. Publicity

Except where prohibited, you consent to our use of your name and the Principal Investigator’s name and title, proposal title, and proposal abstract text for purposes of identifying Amazon’s support of you, the Principal Investigator, the proposal and/or the ARA Program.

You may acknowledge our support by stating that your research is supported by the ARA Program (e.g., “Research reported in this [publication/press release] was supported by an Amazon Research Award, [Cycle /Year].”). Any use of Amazon or AWS logos is subject to the Amazon Trademark Guidelines and AWS Trademark Guidelines, respectively. Any other use of Amazon or AWS logos requires Amazon’s or such affiliate’s prior written consent. You must receive Amazon’s prior written consent before issuing a press release or making any public disclosure regarding your participation in the ARA Program. You agree not to misrepresent or embellish the relationship between us and you. You will not imply any relationship or affiliation between us and you except as expressly permitted by these Rules.

VII. Limitation of Liability

TO THE EXTENT PERMITTED BY APPLICABLE LAW, YOU ACCEPT THE CONDITIONS STATED IN THESE RULES, AGREE TO BE BOUND BY THE DECISIONS OF AMAZON, AND WARRANT THAT YOU ARE ELIGIBLE TO PARTICIPATE IN THE ARA PROGRAM. TO THE EXTENT PERMITTED BY APPLICABLE LAW, YOU, EACH RESEARCH TEAM MEMBER, THE PRINCIPAL INVESTIGATOR AND THE PRINCIPAL INVESTIGATOR’S INSTITUTION HEREBY RELEASES AMAZON FROM, AND WAIVES ANY AND ALL CLAIMS AGAINST AMAZON FOR, ANY LOSSES, LIABILITY, AND DAMAGES OF ANY KIND, (INCLUDING FOR ANY LOSS OF DATA, LOST PROFITS, COST OF COVER OR OTHER SPECIAL, INCIDENTAL, CONSEQUENTIAL, INDIRECT, PUNITIVE, EXEMPLARY OR RELIANCE DAMAGES) INCURRED OR SUSTAINED IN CONNECTION WITH OR ARISING OUT OF (1) THE ARA PROGRAM OR ANY TRAVEL OR ACTIVITY RELATED THERETO, (2) USE OF ANY PROPOSAL OR RIGHTS THEREIN, OR (3) ANY BREACH OF ANY AGREEMENT OR WARRANTY ASSOCIATED WITH THE ARA PROGRAM, INCLUDING THESE RULES, HOWEVER CAUSED AND REGARDLESS OF THEORY OF LIABILITY.

VIII. Changes

We may amend any of these Rules at our sole discretion by posting the revised terms on the ARA Program website. Your continued participation in the ARA Program after the effective date of the revised Rules constitutes your acceptance of the rules.

IX. Disputes

Any dispute or claim relating in any way to the ARA Program will be resolved in accordance with terms set forth in the AWS Agreements.

X. Representations and Warranties

You represent and warrant that:

(a) your receipt of any Award is neither prohibited by nor inconsistent with any applicable laws, regulations, or binding orders, including applicable ethics rules or internal institutional rules;

(b) you have completed or will complete all legal and ethical requirements necessary to accept the Award;

(c) your receipt of the Award will not knowingly create a conflict of interest for Amazon;

(d) the Principal Investigator has not participated in, nor had, and do not anticipate participating in or having, any decision-making authority over, any procurements or purchasing decisions involving Amazon on behalf of your organization during the previous or upcoming twelve (12) months; and

(e) you will properly book and record the Award in your accounting documents in accordance with applicable laws and regulations.

In the event that your representations and warranties under this section are or become inaccurate, you must notify us immediately (research-awards@amazon.com) and any Award your organization receives will be voidable.

US, CA, Palo Alto
The Sponsored Products and Brands team at Amazon Ads is re-imagining the advertising landscape through industry leading generative AI technologies, revolutionizing how millions of customers discover products and engage with brands across Amazon.com and beyond. We are at the forefront of re-inventing advertising experiences, bridging human creativity with artificial intelligence to transform every aspect of the advertising lifecycle from ad creation and optimization to performance analysis and customer insights. We are a passionate group of innovators dedicated to developing responsible and intelligent AI technologies that balance the needs of advertisers, enhance the shopping experience, and strengthen the marketplace. If you're energized by solving complex challenges and pushing the boundaries of what's possible with AI, join us in shaping the future of advertising. Amazon Ads Response Prediction team is your choice, if you want to join a highly motivated, collaborative, and fun-loving team with a strong entrepreneurial spirit and bias for action. We are seeking an experienced and motivated Machine Learning Applied Scientist who loves to innovate at the intersection of customer experience, deep learning, and high-scale machine-learning systems. Amazon Advertising operates at the intersection of eCommerce and advertising, and is investing heavily in building a world-class advertising business. We are defining and delivering a collection of self-service performance advertising products that drive discovery and sales. Our products are strategically important to our Retail and Marketplace businesses driving long-term growth. We deliver billions of ad impressions and millions of clicks daily and are breaking fresh ground to create world-class products to improve both shopper and advertiser experience. With a broad mandate to experiment and innovate, we grow at an unprecedented rate with a seemingly endless range of new opportunities. We are looking for a talented Machine Learning Applied Scientist for our Amazon Ads Response Prediction team to grow the business. We are providing advanced real-time machine learning services to connect shoppers with right ads on all platforms and surfaces worldwide. Through the deep understanding of both shoppers and products, we help shoppers discover new products they love, be the most efficient way for advertisers to meet their customers, and helps Amazon continuously innovate on behalf of all customers. Key job responsibilities As a Machine Learning Applied Scientist, you will: * Conduct deep data analysis to derive insights to the business, and identify gaps and new opportunities * Develop scalable and effective machine-learning models and optimization strategies to solve business problems * Run regular A/B experiments, gather data, and perform statistical analysis * Work closely with software engineers to deliver end-to-end solutions into production * Improve the scalability, efficiency and automation of large-scale data analytics, model training, deployment and serving * Conduct research on new machine-learning modeling to optimize all aspects of Sponsored Products and Brands business About the team We are pioneers in applying advanced machine learning and generative AI algorithms in Sponsored Products and Brands business. We empower every customer with a customized discovery experiences from back-end optimization (such as customized response prediction models) to front-end CX innovation (such as widgets), to help shoppers feel understood and shop efficiently on and off Amazon.
US, WA, Seattle
The Sponsored Products and Brands team at Amazon Ads is re-imagining the advertising landscape through industry leading generative AI technologies, revolutionizing how millions of customers discover products and engage with brands across Amazon.com and beyond. We are at the forefront of re-inventing advertising experiences, bridging human creativity with artificial intelligence to transform every aspect of the advertising lifecycle from ad creation and optimization to performance analysis and customer insights. We are a passionate group of innovators dedicated to developing responsible and intelligent AI technologies that balance the needs of advertisers, enhance the shopping experience, and strengthen the marketplace. If you're energized by solving complex challenges and pushing the boundaries of what's possible with AI, join us in shaping the future of advertising. Key job responsibilities We are looking for an Applied Science Manager to lead the Insights & Prompt Generation vertical within the Conversational Discovery Experiences (CAX) team in Sponsored Products and Brands (SPB). This team owns prompt generation, quality, personalization, and coverage for Sponsored Prompts, a new conversational ad format powered by large language models (LLMs) that helps shoppers discover products across Amazon.com. As an Applied Science Manager, you will lead a team of applied scientists and engineers to build and scale the prompt generation pipeline, develop new prompt themes and quality frameworks, and drive coverage expansion across all surfaces. You will own the science roadmap for prompt generation and personalization. You will define the metrics that measure prompt effectiveness and drive experimentation to improve CTR, helpfulness, and advertiser outcomes. This role requires strong technical depth in NLP, LLMs, and information retrieval, combined with the ability to manage and grow a science team, set research direction, and influence product strategy. You will work across organizational boundaries with engineering, product, and business teams to translate science investments into measurable business impact.
US, CA, Pasadena
The Amazon Center for Quantum Computing in Pasadena, CA, is looking to hire an Applied Scientist specializing in Testing of Control Systems hardware. Working alongside other scientists and engineers, you will validate hardware and software systems performing the control and readout functions for Amazon quantum processors. Working effectively within a cross-functional team environment is critical. The ideal candidate will have an established background in test engineering applicable to large mixed-signal systems. Diverse Experiences Amazon values diverse experiences. Even if you do not meet all of the preferred qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying. Work/Life Balance We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve in the cloud. Inclusive Team Culture Here at AWS, it’s in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences, inspire us to never stop embracing our uniqueness. Mentorship and Career Growth We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional. Key job responsibilities Our scientists and engineers collaborate across diverse teams and projects to offer state of the art, cost effective solutions for the control of Amazon quantum processor systems. You’ll bring a passion for innovation and collaboration to: Develop automated test scripts for mid-volume electronics manufacturing, utilizing high-speed test equipment such as Gsps oscilloscopes, logic analyzers, and network analyzers. Design and implement test plans for high-speed, mixed-signal PCAs and instrument assemblies, covering analog/digital interfaces, ADCs/DACs, FPGAs, and power distribution systems. Develop test requirements and coverage matrices with hardware and software stakeholders, including optimization of test coverage vs test time. Analyze test data to identify failure root causes and trends, implement corrective actions, and drive design-for-testability (DFT) enhancements. Drive continuous test improvement to improve test accuracy, improve final product reliability, and adapt to new measurement requirements.
US, WA, Seattle
This role will contribute to developing the Economics and Science products and services in the Fee domain, with specialization in supply chain systems and fees. Through the lens of economics, you will develop causal links for how Amazon, Sellers and Customers interact. You will be a key and senior scientist, advising Amazon leaders how to price our services. You will work on developing frameworks and scalable, repeatable models supporting optimal pricing and policy in the two-sided marketplace that is central to Amazon's business. The pricing for Amazon services is complex. You will partner with science and technology teams across Amazon including Advertising, Supply Chain, Operations, Prime, Consumer Pricing, and Finance. We are looking for an experienced Economist to improve our understanding of seller Economics, enhance our ability to estimate the causal impact of fees, and work with partner teams to design pricing policy changes. In this role, you will provide guidance to scientists to develop econometric models to influence our fee pricing worldwide. You will lead the development of causal models to help isolate the impact of fee and policy changes from other business actions, using experiments when possible, or observational data when not. Key job responsibilities The ideal candidate will have extensive Economics knowledge, demonstrated strength in practical and policy relevant structural econometrics, strong collaboration skills, proven ability to lead highly ambiguous and large projects, and a drive to deliver results. They will work closely with Economists, Data / Applied Scientists, Strategy Analysts, Data Engineers, and Product leads to integrate economic insights into policy and systems production. Familiarity with systems and services that constitute seller supply chains is a plus but not required. About the team The Stores Economics and Sciences team is a central science team that supports Amazon's Retail and Supply Chain leadership. We tackle some of Amazon's most challenging economics and machine learning problems, where our mandate is to impact the business on massive scale.
US, WA, Seattle
WW Amazon Stores Finance Science (ASFS) works to leverage science and economics to drive improved financial results, foster data backed decisions, and embed science within Finance. ASFS is focused on developing products that empower controllership, improve business decisions and financial planning by understanding financial drivers, and innovate science capabilities for efficiency and scale. We are looking for a data scientist to lead high visibility initiatives for forecasting Amazon Stores' financials. You will develop new science-based forecasting methodologies and build scalable models to improve financial decision making and planning for senior leadership up to VP and SVP level. You will build new ML and statistical models from the ground up that aim to transform financial planning for Amazon Stores. We prize creative problem solvers with the ability to draw on an expansive methodological toolkit to transform financial decision-making with science. The ideal candidate combines data-science acumen with strong business judgment. You have versatile modeling skills and are comfortable owning and extracting insights from data. You are excited to learn from and alongside seasoned scientists, engineers, and business leaders. You are an excellent communicator and effectively translate technical findings into business action. Key job responsibilities Demonstrating thorough technical knowledge, effective exploratory data analysis, and model building using industry standard ML models Working with technical and non-technical stakeholders across every step of science project life cycle Collaborating with finance, product, data engineering, and software engineering teams to create production implementations for large-scale ML models Innovating by adapting new modeling techniques and procedures Presenting research results to our internal research community
US, WA, Seattle
As part of the AWS Applied AI Solutions Core Services organization, we're advancing the frontier of geospatial intelligence and AI-powered spatial reasoning. Our vision is to be the trusted foundation for transforming every business with Amazon AI teammates. Our mission is to deliver turnkey, enterprise-grade foundational AI capabilities that create delightful AI powered solutions. We're building sophisticated AI systems that enable intelligent agents to understand and operate effectively in the physical world through advanced geospatial optimization. Key job responsibilities - Develop geospatial optimization models that generalize across diverse customer use cases in logistics, transportation, and spatial planning - Scope optimization projects with multiple customers in mind, abstracting away complex science problems to create scalable solutions - Discover, evaluate, and adapt existing optimization models and geospatial tools for customer deployment - Develop semantic enrichment methods to integrate heterogeneous data sources including open geospatial data, multimodal sensor data, images, videos, satellite imagery, and documents - Research novel approaches combining AI agents with geospatial optimization to solve complex spatial problems - Collaborate with engineering teams to integrate science components into production systems - Conduct rigorous experimentation and establish evaluation frameworks to measure solution performance A day in the life A day in the life As an Applied Scientist, you'll develop optimization algorithms and AI-powered geospatial solutions while maintaining a clear path to customer impact. You'll investigate novel approaches to spatial optimization, develop methods for semantic data enrichment, and validate ideas through rigorous experimentation with real customer data. You'll collaborate with other scientists and engineers to transform research insights into scalable solutions, work directly with enterprise customers to understand requirements, and help shape the future direction. Leveraging and advancing generative AI technology will be a big part of your charter. About the team Our Applied AI Solutions Core Services Science team is tackling fundamental challenges in geospatial optimization and AI-powered spatial reasoning. We're investigating novel approaches to how AI systems can solve complex logistics and transportation problems, reason about spatial relationships, and integrate diverse data sources to create enterprise-grade geospatial intelligence. Working at the intersection of optimization, large language models, and geospatial data science, we're developing practical techniques that advance the state-of-the-art in geospatial AI.
US, WA, Bellevue
We are looking for detail-oriented, organized, and responsible individuals who are eager to learn how to apply their causal inference and/or structural econometrics skillsets to solve real world problems. The intern will work in the area of Economics Intelligence in Amazon Returns and Recommerce Technology and Innovation and develop new, data-driven solutions to support the most critical components of this rapidly scaling team. Our PhD Economist Internship Program offers hands-on experience in applied economics, supported by mentorship, structured feedback, and professional development. Interns work on real business and research problems, building skills that prepare them for full-time economist roles at Amazon and beyond. You will learn how to build data sets and perform applied econometric analysis collaborating with economists, scientists, and product managers. These skills will translate well into writing applied chapters in your dissertation and provide you with work experience that may help you with placement. These are full-time positions at 40 hours per week, with compensation being awarded on an hourly basis. About the team The WWRR Economics Intelligence (RREI) team brings together Economists, Data Scientists, and Business Intelligence Engineers experts to delivers economic solutions focused on forecasting, causality, attribution, customer behavior for returns, recommerce, and sustainability domains.
US, CA, San Francisco
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.
US, WA, Bellevue
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.
US, WA, Seattle
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.