Social
ARA-Fall26-16x9.png

Fall 2025 Amazon Research Awards recipients announced

Awardees represent more than 49 universities in 11 countries. Recipients have access to Amazon public datasets, along with AWS AI/ML services and tools.

By Amazon Research Awards team
May 27, 2026
9 min read
Share

Amazon Research Awards (ARA) provides unrestricted funds and AWS Promotional Credits to academic researchers investigating various research topics in multiple disciplines. This cycle, ARA received many excellent research proposals from across the world and today is publicly announcing 70 award recipients who represent 49 universities in 11 countries.

This announcement includes awards funded under 6 calls for proposals during the fall 2025 cycle: AI for Information Security, Agentic AI , Automated Reasoning, AWS Cryptography, Cybersecurity and Anti-Abuse Technologies, and Sustainability Proposals were reviewed for the quality of their scientific content and their potential to impact both the research community and society. Additionally, Amazon encourages the publication of research results, presentations of research at Amazon offices worldwide, and the release of related code under open-source licenses.

Recipients have access to more than 700 Amazon public datasets and can utilize AWS AI/ML services and tools through their AWS Promotional Credits. Recipients also are assigned an Amazon research contact who offers consultation and advice, along with opportunities to participate in Amazon events and training sessions.

"Fraud and abuse evolve at the speed of the technologies that bad actors exploit. Since we can only defend against what we can measure, the science of studying those technologies has to keep pace," said Dhruv Kuchhal, Applied Scientist, Special Projects & Invest-Fixed. "Through ARA, we bring together experts across industry and academia to tackle these problems upstream and publish defenses that systematically raise bad actors' operating costs and erode their ROI as they spread across the ecosystem. This not only strengthens Amazon, but the broader Web, including online shopping customers, sellers and brands who build businesses online, and the platforms and payment rails that tie them together. We were impressed by the quality and volume of proposals we received — a strong signal that the field is raising the bar for Web users everywhere — and we look forward to working with the new recipients to turn this research into lasting, ecosystem-wide improvements in fraud and abuse prevention."

“AI is reshaping cybersecurity faster than ever in advancing how we detect threats and defend systems, ”said Wei Ding, Applied Science Manager, GuardDuty, AWS. “At the same time, agentic AI requires stronger guarantees of safety, robustness, and trust worthiness. Since 2020, our team has funded security research that solves some of the biggest challenges for the industry. We’re pleased to continue our tradition of fostering innovation through these latest research projects addressing agentic AI security, AI-powered incident response, and threat detection in agentic AI systems and cloud environments, among other exciting areas.”

ARA funds proposals throughout the year in a variety of research areas. Applicants are encouraged to visit our call for proposals page for more information or send an email to be notified of future open calls.

The tables below list, in alphabetical order by last name, fall 2025 cycle call-for-proposal recipients, sorted by research

AI for Information Security

Recipient

University

Research title

Peng Gao

Virginia Polytechnic Institute and State University

CortexCTI: A Unified Threat Intelligence Engine for Knowledge-Driven Cloud Threat Detection and Response

Guofei Gu

Texas A&M University

New Benchmark and Defense on Prompt Injection in Agentic AI Systems

Xiyang Hu

Arizona State University

Securing Agentic AI: From Local Detection to Global Assurance

Adriana Sejfia

The University of Edinburgh

Exploit-driven AI Agents for vulnerability detection verification

Yue Zhao

University of Southern California

Securing Agentic AI: From Local Detection to Global Assurance

Automated Reasoning

Recipient

University

Research title

Jonathan Aldrich

Carnegie Mellon University

A Visual Debugger for Program Verification

Dalal Alrajeh

Imperial College London

SOLAR: Symbolic Learning for Automated Requirements Consistency

Maria Paola Bonacina

University of Verona

New Data Structure Theories and Quantifiers in CDSAT

Jason Cong

University of California Los Angeles

Breaking the Parallelism Limit with SAT-solving Accelerators

Lucas Cordeiro

The University of Manchester

Combining Formal Methods with Large Language Models in ESBMC: Enabling Automated Program Verification through AI/ML

Werner Dietl

University of Waterloo

Strata-Sphere: Expressive Type Systems and Language Formalizations

Katalin Fazekas

TU Wien

PASSAT: Improved Passing of Assertion Stacks to SAT in Incremental SMT Solvers

Sicun Gao

University of California San Diego

Evaluating and Improving Quantitative Reasoning in LLM Agents Using Sandbox Coding Tasks and Formal Tools

Milos Gligoric

The University of Texas at Austin

Documenting and Recommending Tactics in HOL Light

Ronghui Gu

Columbia University in the City of New York

Scaling Formal Verification of Security Properties for Unmodified System Software

Tyler Josephson

University of Maryland Baltimore County

Autoformalization for Scientific Computing in Lean

Junyi Jessy Li

The University of Texas at Austin

Documenting and Recommending Tactics in HOL Light

Xiaorui Liu

North Carolina State University

Neurosymbolic LLM Reasoning with Symbolical Soundness and Logical Consistency

Azalea Raad

Imperial College London

Soteria in Lean: Mechanising the Next Generation of Symbolic Execution Tools

Dominik Schreiber

Karlsruhe Institute of Technology

Resource-Efficient Flexible SAT Solving in HPC and Cloud Environments

Ilya Sergey

National University of Singapore

Linear Types for a Foundational Multi-Modal Program Verifier

Peter Sewell

University of Cambridge

Gradual Lightweight Methods for High-Assurance Cloud Infrastructure

Paulo Shakarian

Syracuse University

Non-Markovian Agentic Meta-Reasoning

Armando Solar-Lezama

Massachusetts Institute of Technology

Synthesizing Library Models for Static Analysis via LLMs and Conformance Testing

Salil Vadhan

Harvard University

Translating Formal Proofs of Differential Privacy via LLMs

Nickolai Zeldovich

Massachusetts Institute of Technology

Verifying Rust distributed system implementations using monotonic ownership state machines in Verus

Xuezhou Zhang

Boston University

Auto-Formalization and Informalization through Two-Stage Reinforcement Learning

Tianyi Zhang

Purdue University

Scaling Interprocedural Data-Flow Analysis with LLMs

AWS Agentic AI

Recipient

University

Research title

Raman Arora

Johns Hopkins University

Multi-Party Differential Privacy: Unlocking Enterprise Agentic AI

Fanglin Che

Worcester Polytechnic Institute

Autonomous Catalyst Design with Agentic AI for Hydrogen Production

Muhao Chen

University of California Davis

FlowGuard: Evolutionary Red-Teaming for Safe Multimodal Web Agents

Ioannis Demertzis

University of California Santa Cruz

CAMEO: Confidential Agentic Multi-component Enclave Orchestration

Caiwen Ding

University of Minnesota Twin Cities

End-to-End Agentic AI for Scalable Chiplet Design with Extreme Parallelism and Heterogeneity

Ariel Felner

Ben-Gurion University of the Negev

Multi-Agent Pathfinding with Unassigned Agents

Zhaomiao Guo

The University of Texas at Austin

From Observation to Intervention: Counterfactual Multi-Agent World Models for Autonomous Driving

Jiangen He

The University of Tennessee-Knoxville

Beyond Walls of Text: Building UI-Native LLM Agents as the Next Gateway to the Internet

Fan Lai

University of Illinois at Urbana-Champaign

Reinforcing Coordination: Streaming, Exploration, and Distillation for Long-Horizon Agent Learning

Ziyang Li

Johns Hopkins University

A Protocol Stack for Resource-Bound Multi-Agent AI

Henry Liu

University of Michigan

Automating Large Scale Deployment of Infrastructure-based Safety Critical Event Detection with Agentic AI

Bryan Low Kian Hsang

National University of Singapore

Self-Configurable Agentic Learning via Co-optimization

Chinmay Maheshwari

Johns Hopkins University

Markov Near-Potential Function Based MARL Training for Mixed Cooperative–Competitive Agentic AI

Arash Noshadravan

Texas A&M University

A Retrieval-Augmented Dual-Attention Vision Framework for Standards-Aligned Infrastructure Inspection

Muhammad Shafique

New York University Abu Dhabi

AVAAS – Automated Vulnerability Analysis Through Advanced Agentic Systems

Roni Stern

Ben-Gurion University of the Negev

Multi-Agent Pathfinding with Unassigned Agents

Zhengzhong Tu

Texas A&M University

FlowGuard: Evolutionary Red-Teaming for Safe Multimodal Web Agents

Lu Wang

University of Michigan

Benchmarking and Monitoring Multi-Agent Scheming

Yuke Wang

Rice University

Empowering Multimodal AI Agents with Continuous Learning

Hamed Zamani

University of Massachusetts Amherst

A Framework for Proactive and Collaborative AI Agents

Yang Zhao

University of Minnesota Twin Cities

End-to-End Agentic AI for Scalable Chiplet Design with Extreme Parallelism and Heterogeneity

Victor Zhong

University of Waterloo

KNOWLEDGESTORE: A Dynamic Hierarchical Memory for Scalable, Enterprise-Ready AI Agents on AWS

AWS Cryptography

Recipient

University

Research title

Sri AravindaKrishnan Thyagarajan

The University of Sydney

Efficient Robust Post-Quantum Distributed Key Generation and Threshold Signatures

Daniel J. Bernstein

University of Illinois at Chicago

Formally verified symmetric cryptography

Jeremiah Blocki

Purdue University

Stronger Memory Hard Functions to Protect Passwords against Brute Force Attacks

Geoffroy Couteau

Paris Cité University

Pseudorandom Correlations for Threshold Cryptography

Yevgeniy Dodis

New York University

Machine Unlearning and Computational Assumptions for AI

Zhengzhong Jin

Northeastern University - United States of America

Practical Watermarking for LLMs via Pseduorandom Codes

Yael Kalai

Massachusetts Institute of Technology

Enhancing AI Safety Using Cryptography

John Liagouris

Boston University

Pushing secure MPC beyond niche applications

Rafail Ostrovsky

University of California Los Angeles

Towards Low-Latency Maliciously Secure MPC for LLMs

Rachel Player

Royal Holloway - University of London

New Approaches for the Linear Transform in BFV/BGV

Elaine Shi

Carnegie Mellon University

Practical Secure Computation At Scale

Akshayaram Srinivasan

University of Toronto

Simultaneous-Message and Succinct Secure Computation

Douglas Stebila

University of Waterloo

FantASM: Fast, Auditable, and Neat Assembly

Ni Trieu

Arizona State University

Fuzzy Secure Computation for Real-World Noisy Data

Xiao Wang

Northwestern University - United States of America

From Signing to Garbling: Exploring the Spectrum of Post-Quantum Primitives

Mark Zhandry

Stanford University

Algorithms for Post-Quantum Cryptography

Jiaheng Zhang

National University of Singapore

Practical Watermarking for LLMs via Pseduorandom Codes

Vassilis Zikas

Georgia Institute of Technology

Fuzzy Secure Computation for Real-World Noisy Data

Cybersecurity and Anti-Abuse Technologies

Recipient

University

Research title

Geoffrey Voelker

University of California San Diego

Detecting Anti-detect Browsers at Scale

Devices Sustainability

Recipient

University

Research title

Udit Gupta

Cornell University

Agent-Driven Life Cycle Carbon Optimization for Sustainable Edge Devices

Adriana Schulz

Brown University

Integrating Sustainability Reasoning into Early-Stage Electronics Design
Tags
About the Author
Amazon Research Awards team

Related content

Work with us

See more jobs See more jobs
Applied Scientist, AWS Automated Reasoning
US, WA, Seattle
Applied Scientists in AWS Automated Reasoning are dedicated to making AWS the best computing service in the world for customers who require advanced and rigorous solutions for automated reasoning, privacy, and sovereignty. Key job responsibilities The successful candidate will: - Solve large or significantly complex problems that require deep knowledge and understanding of your domain and scientific innovation. - Own strategic problem solving, and take the lead on the design, implementation, and delivery for solutions that have a long-term quantifiable impact. - Provide cross-organizational technical influence, increasing productivity and effectiveness by sharing your deep knowledge and experience. - Develop strategic plans to identify fundamentally new solutions for business problems. - Assist in the career development of others, actively mentoring individuals and the community on advanced technical issues. A day in the life This is a unique and rare opportunity to get in early on a fast-growing segment of AWS and help shape the technology, product and the business. You will have a chance to utilize your deep technical experience within a fast moving, start-up environment and make a large business and customer impact. About the team Diverse Experiences Amazon Automated Reasoning 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 Amazon Automated Reasoning? At Amazon, automated reasoning is central to maintaining customer trust and delivering delightful customer experiences. Our organization is responsible for creating and maintaining a high bar for automated reasoning across all of Amazon's products and services. We offer talented automated reasoning professionals the chance to accelerate their careers with opportunities to build experience in a wide variety of areas including cloud, devices, retail, entertainment, healthcare, operations, and physical stores. Inclusive Team Culture In Amazon Automated Reasoning, it's in our nature to learn and be curious. Ongoing DEI events and learning experiences inspire us to continue learning and to embrace our uniqueness. Addressing the toughest automated reasoning challenges requires that we seek out and celebrate a diversity of ideas, perspectives, and voices. Training & 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, training, and other career-advancing resources here to help you develop into a better-rounded professional. Work/Life Balance We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why flexible work hours and arrangements are part of our culture. When we feel supported in the workplace and at home, there's nothing we can't achieve.
Sr. Applied Scientist, AWS Automated Reasoning
US, WA, Seattle
Applied Scientists in AWS Automated Reasoning are dedicated to making AWS the best computing service in the world for customers who require advanced and rigorous solutions for automated reasoning, privacy, and sovereignty. Key job responsibilities The successful candidate will: - Solve large or significantly complex problems that require deep knowledge and understanding of your domain and scientific innovation. - Own strategic problem solving, and take the lead on the design, implementation, and delivery for solutions that have a long-term quantifiable impact. - Provide cross-organizational technical influence, increasing productivity and effectiveness by sharing your deep knowledge and experience. - Develop strategic plans to identify fundamentally new solutions for business problems. - Assist in the career development of others, actively mentoring individuals and the community on advanced technical issues. A day in the life This is a unique and rare opportunity to get in early on a fast-growing segment of AWS and help shape the technology, product and the business. You will have a chance to utilize your deep technical experience within a fast moving, start-up environment and make a large business and customer impact. About the team Diverse Experiences Amazon Automated Reasoning 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 Amazon Automated Reasoning? At Amazon, automated reasoning is central to maintaining customer trust and delivering delightful customer experiences. Our organization is responsible for creating and maintaining a high bar for automated reasoning across all of Amazon's products and services. We offer talented automated reasoning professionals the chance to accelerate their careers with opportunities to build experience in a wide variety of areas including cloud, devices, retail, entertainment, healthcare, operations, and physical stores. Inclusive Team Culture In Amazon Automated Reasoning, it's in our nature to learn and be curious. Ongoing DEI events and learning experiences inspire us to continue learning and to embrace our uniqueness. Addressing the toughest automated reasoning challenges requires that we seek out and celebrate a diversity of ideas, perspectives, and voices. Training & 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, training, and other career-advancing resources here to help you develop into a better-rounded professional. Work/Life Balance We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why flexible work hours and arrangements are part of our culture. When we feel supported in the workplace and at home, there's nothing we can't achieve.
Applied Scientist, Fauna
US, CA, Sunnyvale
We are seeking an Applied Scientist to focus on Robotics Spatial Intelligence and Semantic Understanding. In this role, you'll research and build advanced semantic and world understanding algorithms that enable robots to observe, understand, and reason about complex and dynamic home environments. You'll work across a broad spectrum of 3D perception, contextual understanding, and world modeling approaches to build robust solutions that support autonomous decision making, task planning, navigation, and manipulation. Key job responsibilities - Develop and implement robust World Understanding and Modeling algorithms for a domestic robot. - Build simulation-based and on-robot evaluation frameworks with comprehensive benchmarks and metrics for systematic evaluation of Our Spatial Intelligence stack. - Conduct sim-to-real transfer experiments, analyzing performance gaps and developing techniques to ensure reliable real-world performance. - Collaborate with navigation, manipulation, and other teams to ensure seamless integration of World Understanding capabilities. - Stay current with the latest advances in World Modeling, Spatial Reasoning, and related fields and apply relevant findings to improve system performance About the team Fauna Robotics, an Amazon company, is building capable, safe, and genuinely delightful robots for everyday life. Our goal is simple: make robots people actually want to live and interact with in everyday human spaces. We believe that future won’t arrive until building for robotics becomes far more accessible. Today, too much effort is spent reinventing the fundamentals. We’re changing that by developing tightly integrated hardware and software systems that make it faster, safer, and more intuitive to create real-world robotic products. Our work spans the full stack: mechanical design, control systems, dynamic modeling, and intelligent software. The focus is not just functionality, but experience. We’re building robots that feel responsive, expressive, and genuinely useful. At Fauna, you’ll work at the frontier of this space, helping define how robots move, manipulate, and interact with people in natural environments. It’s an opportunity to solve hard problems across hardware and software with a team focused on making robotics accessible and joyful to build. If you care about making robotics real for everyone and building systems that are as delightful as they are capable, we’re interested in hearing from you.
Data Scientist II, Rapid & Rural Logistics (R2L) Science & AI
US, WA, Bellevue
The R2L team is responsible for building the next generation supply chain for Amazon’s world-class ultra-fast customer experiences including Amazon Fresh groceries, Sub-Same Day, Amazon Now, and other soon-to-launch exciting new businesses. Join us and you'll be taking part in serving our customers in as fast as 30 minutes! R2L Science & AI team sits under R2L and is a central team for all Data Science/AI related asks. We are looking for an experienced and curious data scientist with effective superior analytical skills to inform the data science charter of the team. Key job responsibilities We are looking for an experienced and curious data scientist with effective superior analytical skills to inform the data science charter of the team. This position is critical in helping us learn more about our data and finding opportunities to delight customers with data driven insights and machine learning models. The Data Science and Analytics team owns data science, data engineering, and business intelligence. You will be supporting multiple business and technical stakeholders with high velocity analytics. This role is uniquely positioned in the team as we have a growing need for looking around corners, prioritizing opportunities using data driven insights, and finding solutions to these opportunities using different machine learning techniques and causal inference models. You will be diving deep in our data and have a strong bias for action to quickly produce high quality data analyses with clear findings and recommendations. As part of our journey to learn about our data, some opportunities may be a dead end and you will be balancing unknowns with delivering results for our customers. A day in the life If you are not sure that every qualification on the list above describes you exactly, we'd still love to hear from you! At Amazon, we value people with unique backgrounds, experiences, and skillsets. If you’re passionate about this role and want to make an impact on a global scale, please apply! 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 Learn more about our benefits here: https://amazon.jobs/en/internal/benefits/us-benefits-and-stock
Airspace Management Simulation Applied Scientist, Prime Air Flight Sciences High Fidelity Methods
US, WA, Seattle
Here at Amazon, we embrace our differences. We are committed to furthering our culture of diversity and inclusion of our teams within the organization. How do you get items to customers quickly, cost-effectively, and—most importantly—safely, in less than an hour? And how do you do it in a way that can scale? Our teams of hundreds of scientists, engineers, aerospace professionals, and futurists have been working hard to do just that! We are delivering to customers, and are excited for what’s to come. Check out more information about Prime Air on the About Amazon blog (https://www.aboutamazon.com/news/transportation/amazon-prime-air-delivery-drone-reveal-photos). If you are seeking an iterative environment where you can drive innovation, apply state-of-the-art technologies to solve real world delivery challenges, and provide benefits to customers, Prime Air is the place for you. Come work on the Amazon Prime Air Team! We're looking for a Research Scientist with a background in developing simulations for traffic management algorithms, including expert knowledge in strategic deconfliction, tactical deconfliction, or detect-and-avoid systems. Managing a large number of concurrent autonomous drone flights that share airspace with other autonomous or manned aircraft is a challenging problem. Be part of the team building simulation tools and algorithms to solve this at scale. This role will contribute to a portfolio of simulation tools managing concurrent airspace traffic for aviation systems. This will include developing new methodologies in the areas of conflict detection and resolution, as well as developing related software systems that will be used in operation to enable package delivery at scale. The ideal candidate is comfortable with risk-taking and ambiguity and able to build consensus on critical, controversial technical decisions. If you enjoy the process of solving real-world problems that haven’t been solved at scale anywhere before, Prime Air is right for you. Along the way, we guarantee you’ll get opportunities to be a disruptor, prolific innovator, and a reputed problem solver and directly impact Amazon’s customers worldwide. Key job responsibilities The primary focus of this role will be on modeling traffic management frameworks that use a layered conflict detection and resolution strategy to ensure safe and efficient flight operations. This will include developing fundamental simulation infrastructure code, including discrete event simulation tooling. In addition, it will involve developing expert knowledge of the layers of mitigation and conducting in-depth scientific research on alternative solutions for conflict resolution. The candidate will contribute to significant and impactful systems that will provide value for Amazon customers and will drive these projects from the concept stage through development. This role will include substantial software development in prototyping and production environments.
Applied Scientist II, Alexa Ads
IN, KA, Bengaluru
Alexa+ is the world’s best Generative AI powered personal assistant / agent for consumers, and is becoming the conversational AI interface for Amazon services with the launch of Alexa for Shopping on Amazon.com and Amazon mobile app. At Alexa Ads, we are creating industry's first and most advanced Agentic Advertising products to drive Agentic Commerce. We are seeking an Applied Scientist to join our newly expanding team in India focused on Alexa Agentic/Conversational Ads and Personalization. In this role, you will build machine learning models that seamlessly and naturally integrate relevant advertising into the Alexa experience while deeply personalizing user interactions. You will work closely with other scientists, engineers, and product managers to take models from conception to production. Key job responsibilities - Design, develop, and evaluate innovative machine learning and deep learning models for natural language processing (NLP), recommendation systems, and personalization. - Conduct hands-on data analysis and build scalable ML pipelines. - Design and run A/B experiments to measure the impact of new models on customer experience and ad performance. - Collaborate with software development engineers to deploy models into high-scale, real-time production environments. About the team We are building a new science team in Bangalore to solve some of the most impactful problems in computational advertising. This isn't about tweaking existing models as we are rethinking how ads are ranked, priced, and personalized across voice-first and screen-first surfaces. These are problems that don't have textbook solutions. Key points to note about the team: 🧪 Greenfield team - you are not joining a mature org with rigid processes. You will shape the science roadmap, pick the problems, and define the culture from day one. 📈 Direct business impact — your models directly drive revenue. No yearly cycles to see if your work matters. 🌏 Global scope, local autonomy — collaborate with scientists and engineers across Seattle, Sunnyvale, and Bangalore, but own your problem space end-to-end. 🎓 Ship AND Publish: We encourage top-tier publications (NeurIPS, ACL, EMNLP, KDD, ICML, WWW) while ensuring your research hits production.
Applied scientist, Agentic AI, AWS Agentic AI
IL, Tel Aviv
Come join the AWS Agentic AI science team in building the next generation models for intelligent automation. 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 that will give Applied Scientists like you endless opportunities to see your 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. As part of the team, we expect that you will develop innovative solutions to hard problems, and publish your findings at peer reviewed conferences and workshops. We are looking for world class researchers with experience in one or more of the following areas - autonomous agents, API orchestration, Planning, large multimodal models (especially vision-language models), reinforcement learning (RL) and sequential decision making.
Sr Applied Scientist, Support Agent Intelligence and Evaluation
US, WA, Seattle
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. Millions of advertisers rely on Amazon's self-service support experience to resolve issues, unblock campaigns, and grow their business. Our Support Agents team is building the science behind intelligent, conversational support — systems that understand advertiser intent, retrieve the right knowledge, generate accurate answers, and know when to escalate. We serve ~2M monthly active advertisers across dozens of locales and languages, and every percentage point of improvement in resolution quality translates directly into advertiser success and retention. We are seeking an Applied Scientist who is passionate about building evaluation science, NLP systems, and quality measurement at scale. You will define how we measure "good" — designing LLM-as-a-judge evaluation pipelines, developing our next-generation Issue Resolution Rate (IRR) metrics, and closing the quality gap between English and non-English markets. Your work will directly shape what ships to advertisers and what leadership uses to assess the health of our support experience. Key job responsibilities 1. Enhance support agent capabilities across the broad suite of Amazon Advertising products — expanding coverage, depth of resolution, and advertiser task completion across Sponsored Products, Sponsored Brands, DSP, AMC, and more 2. Design and own the evaluation framework for agent quality — including automated LLM-based scoring of answer correctness, confidence calibration, and conversation-level resolution signals 3. Develop novel metrics that capture whether advertisers actually got the help they needed (beyond surface-level deflection rates) 4. Build and improve retrieval and generation models that power real-time advertiser interactions under strict latency SLAs 5. Drive multilingual science — improve non-English resolution rates through cross-lingual retrieval, translation quality modeling, and locale-aware evaluation 6. Partner with product, engineering, and business teams to productize research and inform roadmap decisions with data A day in the life You might start the morning reviewing overnight evaluation results from your LLM-as-a-judge pipeline, then jump into a whiteboard session designing a new resolution metric that captures whether advertisers actually unblocked their campaign. After lunch you're running offline experiments on a cross-lingual retrieval model to close the quality gap for non-English markets, and by end of day you're syncing with engineering on latency trade-offs for next week's A/B test. The constant: your science directly changes the experience millions of advertisers have when they need help. About the team This role sits within Amazon Advertising's broader Agentic Intelligence organization — a community of multiple Applied Science and Engineering teams building the next generation of AI-powered experiences for advertisers. You'll have access to Principal Engineers and Principal Applied Scientists to pressure-test ideas and elevate your work. What makes this team unique is the balance: you'll drive product-facing science through customer support agents that touch millions of advertisers, while also influencing and collaborating with a core AI infrastructure team within Amazon. The team is cross-functional — scientists and engineers work shoulder-to-shoulder, from problem framing through production deployment.
Research Scientist III - AMZ10061595
US, WA, Seattle
MULTIPLE POSITIONS AVAILABLE Employer: AMAZON DEVELOPMENT CENTER U.S., INC. Offered Position: Research Scientist III Job Location: Seattle, Washington Job Number: AMZ10061595 Position Responsibilities: Develop and apply state of the art machine learning methods to large, multi source datasets to build and implement risk prevention, detection and mitigation solutions. Contribute to the development of ML Ops infrastructure, as well as the creation and delivery of Amazon’s science roadmap, including Gen AI efforts. Work closely with software engineering teams to deploy innovations. Mentor and coach junior scientists, including through lunch-and-learn sessions, tech talks, and regular office hours. Publish insights in and champion industry best practices at internal and external journals and conferences. Position Requirements: Master’s degree or foreign equivalent degree in Computer Science, Engineering, Mathematics, or a related field and three years of experience in the job offered or a related occupation. Employer will accept a bachelor’s degree or foreign equivalent degree in Computer Science, Engineering, Mathematics, or a related field and five years of progressive postbaccalaureate experience in the job offered or a related occupation as equivalent to a master’s degree and three years of experience. Must have three years of experience in the following skill(s): (1) conducting research in machine learning, natural language processing, computer vision, or a related functionality, and publishing findings; (2) building machine learning models including generative models for business applications, and (3) programming in Java, C++, Python or related language. Amazon.com is an Equal Opportunity-Affirmative Action Employer – Minority / Female / Disability / Veteran / Gender Identity / Sexual Orientation. 40 hours / week, 8:00am-5:00pm, Salary Range $164,955/year to $215,300/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#0000
Applied Scientist, Special Projects
US, WA, Seattle
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 limits. If you’re interested in innovating at scale to address big challenges in the world, this is the team for you. As an Applied Scientist on our team, you will focus on building state-of-the-art ML models for biology. Our team rewards 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 forefront of both academic and applied research in this product area, you have the opportunity to work together with a diverse and talented team of scientists, engineers, and product managers and collaborate with other teams.
See more jobs
View from space of a connected network around planet Earth representing the Internet of Things.
Get more from Amazon Science
Subscribe to our newsletter

Amazon.com | Conditions of Use | Privacy | © 1996-2026 Amazon.com, Inc. or its affiliates

Social