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Frequently asked questions

In addition to the FAQs below, please view the ARA Program Rules.
General
General
What research areas does ARA fund?
ARA funds in a variety of research areas relevant to Amazon, such as applied machine learning, automated reasoning, computer vision, fairness in artificial intelligence, machine learning algorithms and theory, natural language processing, robotics, security, sustainability and more. Please refer to the detailed CFPs for more information.
What types of proposals does ARA fund?
The Amazon Research Awards (ARA) program funds academic research and related contributions to open-source projects by top academic researchers around the world.
What is the structure of an ARA award? Can it be extended?
Awards are structured as one-time unrestricted gifts to the Principal Investigator's academic institution or organization, and can include cash and AWS Promotional Credits. Though this funding is not extendable, applicants can submit new proposals for subsequent calls.
Applying for an award
How do I apply?
Please follow the instructions on the specific CFP you are applying to.
Who is eligible to apply?
Researchers from around the world are encouraged to apply. Please refer to the ARA Program Rules for eligibility.
What are the timelines for proposal submissions and decisions?
We evaluate research proposals and provide decisions via email to all applicants approximately three months after the submission deadline. Please follow the timeline on the specific CFP you are applying to.
What is an Amazon contact and is one required to apply?
An Amazon contact is an Amazon employee who is aware of the proposal, familiar with the Principal Investigator’s research and may be willing to serve as an Amazon research contact for the proposal, if it is selected. An Amazon contact is not required to submit a proposal. While the ARA team is not able to provide an Amazon contact for the PI prior to submission, all funded proposals will be assigned an Amazon research contact by the review panel.
Is it possible to have multiple faculty members on a single proposal?
Each proposal application should be submitted by a single faculty member, who will serve as the Primary PI. One co-PI per proposal can be included in the application form. ARA defines a co-PI as an individual equally accountable for research performance and management of funding. Formal co-PI’s must be a full-time faculty/permanent researcher and meet ARA eligibility requirements. Other members of the research team can and should be mentioned within the proposal.
Is it possible for one faculty member to be on multiple grants?
Principle Investigators can only submit one proposal at each deadline. A Primary PI can be listed as a co-PI on an additional proposal, but must withdraw if the other proposal is selected. It’s also possible that another CFP may decide to fund your research, if it meets the scope of that CFP.
What budget expenses should I include in my proposal submission?
A proposed cash budget is generally expected to support one to two graduate students (or a post-doctoral researcher) for one year, plus some conference travel and equipment. The budget should include a list of expected costs specified in USD and is not required to include administrative overhead costs. The final award amount will be determined by the awards panel. Please refer to the CFP for specific budget guidelines.


Additionally, proposals may include a request for AWS Promotional Credits1. Proposals should include the requested amount, a short justification, a list of AWS products and any AWS Public Datasets to be used in the proposed research. The final amount of free AWS Promotional Credits will be determined by the awards panel.


1. Please note that your use of any AWS Promotional Credit is subject to the general AWS Customer Agreement terms or other terms governing your use of AWS Services (“Agreement”). In the event of a conflict between these Rules and the Agreement, the Agreement will control with respect to your access to and use of the Service Offerings. Additionally, any use of AWS Promotional Credit will be in accordance with and subject to the AWS Promotional Credit Terms & Conditions. In the event of a conflict between these Rules and the AWS Promotional Credit Terms & Conditions, the AWS Promotional Credit Terms & Conditions will govern with respect to any AWS Promotional Credit you receive.
Proposal review process
Who evaluates the proposals and when will I know the outcome?
Project proposals are reviewed by an internal awards panel and the results are communicated approximately three months after the submission deadline. We will communicate the decision to the primary PI listed on each proposal, and will make an announcement on the ARA website. We expect the primary PI to notify the rest of their team about funding decisions.
Will I be able to find out why my proposal was not accepted?
Unfortunately, due to the number of proposals we receive, we are unable to provide detailed reasons a proposal was not accepted.
Award information
What happens after the ARA recipients are announced?
Each project will be assigned an Amazon research contact. The researchers are encouraged to maintain regular communication with their Amazon contact to discuss ongoing research and project progress. We also encourage publishing the outcome of the project and committing any related code to open-source code repositories.
Does Amazon retain any intellectual property and licensing on the material developed during the time period that a student is funded?
ARA funding is distributed as unrestricted gifts to universities. As such, the funding does not result in any transfer or license of any intellectual property rights. Please refer to the ARA Program Rules for more information.
Do recipients have access to Amazon data?
Recipients will have access to Amazon datasets that are already public, such as the Amazon Bin Image Dataset, but not to non-public data.
Does Amazon accept any legal obligation with respect to submitted proposals?
We are happy to review non-confidential project proposals. As such, project proposals shall not contain any confidential information (please do not include any information in your proposal that you or others consider 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 similar ideas in the future without restriction or obligation. Please refer to the ARA Program Rules for more information.
Other
How can I contact the ARA team?
We provide limited email support via research-awards@amazon.com. Due to the volume of emails we receive, we may not be able to respond to questions where the answer is available on the website.
How can I find out about future ARA calls for proposals?
Please email research-awards@amazon.com to be added to the CFP email announcement.
Is the AWS Machine Learning Research Awards (MLRA) part of ARA?
Yes, in 2020 the two programs merged and MLRA now funds awards through ARA, under the AWS AI call for proposal.
Does Amazon provide any other funding opportunities?
Yes, please visit the collaborations page for more information.

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Applied Scientist II, Industrial Robotics Group
US, MA, N.reading
Amazon Industrial Robotics Group is seeking exceptional talent to help develop the next generation of advanced robotics systems that will transform automation at Amazon's scale. We're building revolutionary robotic systems that combine cutting-edge AI, sophisticated control systems, and advanced mechanical design to create adaptable automation solutions capable of working safely alongside humans in dynamic environments. This is a unique opportunity to shape the future of robotics and automation at an unprecedented scale, working with world-class teams pushing the boundaries of what's possible in robotic dexterous manipulation, locomotion, and human-robot interaction. This role presents an opportunity to shape the future of robotics through innovative applications of deep learning and large language models. At Amazon Industrial Robotics Group, we leverage advanced robotics, machine learning, and artificial intelligence to solve complex operational challenges at an unprecedented scale. Our fleet of robots operates across hundreds of facilities worldwide, working in sophisticated coordination to fulfill our mission of customer excellence. We are pioneering the development of dexterous manipulation system that: - Enables unprecedented generalization across diverse tasks - Enables contact-rich manipulation in different environments - Seamlessly integrates low-level skills and high-level behaviors - Leverage mechanical intelligence, multi-modal sensor feedback and advanced control techniques. The ideal candidate will contribute to research that bridges the gap between theoretical advancement and practical implementation in robotics. You will be part of a team that's revolutionizing how robots learn, adapt, and interact with their environment. Join us in building the next generation of intelligent robotics systems that will transform the future of automation and human-robot collaboration. A day in the life - Work on design and implementation of methods for Visual SLAM, navigation and spatial reasoning - Leverage simulation and real-world data collection to create large datasets for model development - Develop a hierarchical system that combines low-level control with high-level planning - Collaborate effectively with multi-disciplinary teams to co-design hardware and algorithms for dexterous manipulation
Senior Applied Scientist, Fauna
US, NY, New York
We are seeking an Applied Scientist to lead the development of evaluation frameworks and data collection protocols for robotic capabilities. In this role, you will focus on designing how we measure, stress-test, and improve robot behavior across a wide range of real-world tasks. Your work will play a critical role in shaping how policies are validated and how high-quality datasets are generated to accelerate system performance. You will operate at the intersection of robotics, machine learning, and human-in-the-loop systems, building the infrastructure and methodologies that connect teleoperation, evaluation, and learning. This includes developing evaluation policies, defining task structures, and contributing to operator-facing interfaces that enable scalable and reliable data collection. The ideal candidate is highly experimental, systems-oriented, and comfortable working across software, robotics, and data pipelines, with a strong focus on turning ambiguous capability goals into measurable and actionable evaluation systems. Key job responsibilities - Design and implement evaluation frameworks to measure robot capabilities across structured tasks, edge cases, and real-world scenarios - Develop task definitions, success criteria, and benchmarking methodologies that enable consistent and reproducible evaluation of policies - Create and refine data collection protocols that generate high-quality, task-relevant datasets aligned with model development needs - Build and iterate on teleoperation workflows and operator interfaces to support efficient, reliable, and scalable data collection - Analyze evaluation results and collected data to identify performance gaps, failure modes, and opportunities for targeted data collection - Collaborate with engineering teams to integrate evaluation tooling, logging systems, and data pipelines into the broader robotics stack - Stay current with advances in robotics, evaluation methodologies, and human-in-the-loop learning to continuously improve internal approaches - Lead technical projects from conception through production deployment - Mentor junior scientists and engineers
Data Scientist II, Amazon Business
US, WA, Seattle
Come be a part of a rapidly expanding $35 billion-dollar global business. At Amazon Business, a fast-growing startup passionate about building solutions, we set out every day to innovate and disrupt the status quo. We stand at the intersection of tech & retail in the B2B space developing innovative purchasing and procurement solutions to help businesses and organizations thrive. At Amazon Business, we strive to be the most recognized and preferred strategic partner for smart business buying. Bring your insight, imagination and a healthy disregard for the impossible. Join us in building and celebrating the value of Amazon Business to buyers and sellers of all sizes and industries. Unlock your career potential. Amazon Business Data Insights and Analytics team is looking for a Data Scientist to lead the research and thought leadership to drive our data and insights strategy for Amazon Business. This role is central in shaping the definition and execution of the long-term strategy for Amazon Business. You will be responsible for researching, experimenting and analyzing predictive and optimization models, designing and implementing advanced detection systems that analyze customer behavior at registration and throughout their journey. You will work on ambiguous and complex business and research science problems with large opportunities. You'll leverage diverse data signals including customer profiles, purchase patterns, and network associations to identify potential abuse and fraudulent activities. You are an analytical individual who is comfortable working with cross-functional teams and systems, working with state-of-the-art machine learning techniques and AWS services to build robust models that can effectively distinguish between legitimate business activities and suspicious behavior patterns You must be a self-starter and be able to learn on the go. Excellent written and verbal communication skills are required as you will work very closely with diverse teams. Key job responsibilities - Interact with business and software teams to understand their business requirements and operational processes - Frame business problems into scalable solutions - Adapt existing and invent new techniques for solutions - Gather data required for analysis and model building - Create and track accuracy and performance metrics - Prototype models by using high-level modeling languages such as R or in software languages such as Python. - Familiarity with transforming prototypes to production is preferred. - Create, enhance, and maintain technical documentation
Comm Systems Engineer, Wireless Systems
US, TX, Austin
Amazon Leo is an initiative to launch a constellation of Low Earth Orbit satellites that will provide low-latency, high-speed broadband connectivity to unserved and underserved communities around the world. As a Systems Engineer, this role is primarily responsible for the design, development and integration of communication payload and customer terminal systems. The Role: Be part of the team defining the overall communication system and architecture of Amazon Leo’s broadband wireless network. This is a unique opportunity to innovate and define groundbreaking wireless technology at global scale. The team develops and designs the communication system for Leo and analyzes its overall system level performance such as for overall throughput, latency, system availability, packet loss etc. This role in particular will be responsible for leading the effort in designing and developing advanced technology and solutions for communication system. This role will also be responsible developing advanced physical layer + protocol stacks systems as proof of concept and reference implementation to improve the performance and reliability of the LEO network. In particular this role will be responsible for using concepts from digital signal processing, information theory, wireless communications to develop novel solutions for achieving ultra-high performance LEO network. This role will also be part of a team and develop simulation tools with particular emphasis on modeling the physical layer aspects such as advanced receiver modeling and abstraction, interference cancellation techniques, FEC abstraction models etc. This role will also play a critical role in the integration and verification of various HW and SW sub-systems as a part of system integration and link bring-up and verification. Export Control Requirement: Due to applicable export control laws and regulations, candidates must be a U.S. citizen or national, U.S. permanent resident (i.e., current Green Card holder), or lawfully admitted into the U.S. as a refugee or granted asylum.
Applied Scientist, Artificial General Intelligence, AGI Data Services
US, MA, Boston
The Artificial General Intelligence (AGI) team is seeking a dedicated, skilled, and innovative Applied Scientist with a robust background in machine learning, statistics, quality assurance, auditing methodologies, and automated evaluation systems to ensure the highest standards of data quality, to build industry-leading technology with Large Language Models (LLMs) and multimodal systems. Key job responsibilities As part of the AGI team, an Applied Scientist will collaborate closely with core scientist team developing Amazon Nova models. They will lead the development of comprehensive quality strategies and auditing frameworks that safeguard the integrity of data collection workflows. This includes designing auditing strategies with detailed SOPs, quality metrics, and sampling methodologies that help Nova improve performances on benchmarks. The Applied Scientist will perform expert-level manual audits, conduct meta-audits to evaluate auditor performance, and provide targeted coaching to uplift overall quality capabilities. A critical aspect of this role involves developing and maintaining LLM-as-a-Judge systems, including designing judge architectures, creating evaluation rubrics, and building machine learning models for automated quality assessment. The Applied Scientist will also set up the configuration of data collection workflows and communicate quality feedback to stakeholders. An Applied Scientist will also have a direct impact on enhancing customer experiences through high-quality training and evaluation data that powers state-of-the-art LLM products and services. A day in the life An Applied Scientist with the AGI team will support quality solution design, conduct root cause analysis on data quality issues, research new auditing methodologies, and find innovative ways of optimizing data quality while setting examples for the team on quality assurance best practices and standards. Besides theoretical analysis and quality framework development, an Applied Scientist will also work closely with talented engineers, domain experts, and vendor teams to put quality strategies and automated judging systems into practice.
Applied Scientist, Artificial General Intelligence, AGI Data Services
US, MA, Boston
The Artificial General Intelligence (AGI) team is seeking a dedicated, skilled, and innovative Applied Scientist with a robust background in machine learning, statistics, quality assurance, auditing methodologies, and automated evaluation systems to ensure the highest standards of data quality, to build industry-leading technology with Large Language Models (LLMs) and multimodal systems. Key job responsibilities As part of the AGI team, an Applied Scientist will collaborate closely with core scientist team developing Amazon Nova models. They will lead the development of comprehensive quality strategies and auditing frameworks that safeguard the integrity of data collection workflows. This includes designing auditing strategies with detailed SOPs, quality metrics, and sampling methodologies that help Nova improve performances on benchmarks. The Applied Scientist will perform expert-level manual audits, conduct meta-audits to evaluate auditor performance, and provide targeted coaching to uplift overall quality capabilities. A critical aspect of this role involves developing and maintaining LLM-as-a-Judge systems, including designing judge architectures, creating evaluation rubrics, and building machine learning models for automated quality assessment. The Applied Scientist will also set up the configuration of data collection workflows and communicate quality feedback to stakeholders. An Applied Scientist will also have a direct impact on enhancing customer experiences through high-quality training and evaluation data that powers state-of-the-art LLM products and services. A day in the life An Applied Scientist with the AGI team will support quality solution design, conduct root cause analysis on data quality issues, research new auditing methodologies, and find innovative ways of optimizing data quality while setting examples for the team on quality assurance best practices and standards. Besides theoretical analysis and quality framework development, an Applied Scientist will also work closely with talented engineers, domain experts, and vendor teams to put quality strategies and automated judging systems into practice.
Applied Scientist, Artificial General Intelligence, AGI Data Services
US, MA, Boston
The Artificial General Intelligence (AGI) team is seeking a dedicated, skilled, and innovative Applied Scientist with a robust background in machine learning, statistics, quality assurance, auditing methodologies, and automated evaluation systems to ensure the highest standards of data quality, to build industry-leading technology with Large Language Models (LLMs) and multimodal systems. Key job responsibilities As part of the AGI team, an Applied Scientist will collaborate closely with core scientist team developing Amazon Nova models. They will lead the development of comprehensive quality strategies and auditing frameworks that safeguard the integrity of data collection workflows. This includes designing auditing strategies with detailed SOPs, quality metrics, and sampling methodologies that help Nova improve performances on benchmarks. The Applied Scientist will perform expert-level manual audits, conduct meta-audits to evaluate auditor performance, and provide targeted coaching to uplift overall quality capabilities. A critical aspect of this role involves developing and maintaining LLM-as-a-Judge systems, including designing judge architectures, creating evaluation rubrics, and building machine learning models for automated quality assessment. The Applied Scientist will also set up the configuration of data collection workflows and communicate quality feedback to stakeholders. An Applied Scientist will also have a direct impact on enhancing customer experiences through high-quality training and evaluation data that powers state-of-the-art LLM products and services. A day in the life An Applied Scientist with the AGI team will support quality solution design, conduct root cause analysis on data quality issues, research new auditing methodologies, and find innovative ways of optimizing data quality while setting examples for the team on quality assurance best practices and standards. Besides theoretical analysis and quality framework development, an Applied Scientist will also work closely with talented engineers, domain experts, and vendor teams to put quality strategies and automated judging systems into practice.
Senior Applied Scientist, Applied AI
US, WA, Bellevue
We are seeking a passionate, talented, and inventive individual to join the Applied AI team and help build industry-leading technologies that customers will love. This team offers a unique opportunity to make a significant impact on the customer experience and contribute to the design, architecture, and implementation of a cutting-edge product. The mission of the Applied AI team is to enable organizations within Worldwide Amazon.com Stores to accelerate the adoption of AI technologies across various parts of our business. We are looking for a Senior Applied Scientist to join our Applied AI team to work on LLM-based solutions. On our team you will push the boundaries of ML and Generative AI techniques to scale the inputs for hundreds of billions of dollars of annual revenue for our eCommerce business. If you have a passion for AI technologies, a drive to innovate and a desire to make a meaningful impact, we invite you to become a valued member of our team. You will be responsible for developing and maintaining the systems and tools that enable us to accelerate knowledge operations and work in the intersection of Science and Engineering. You will push the boundaries of ML and Generative AI techniques to scale the inputs for hundreds of billions of dollars of annual revenue for our eCommerce business. If you have a passion for AI technologies, a drive to innovate and a desire to make a meaningful impact, we invite you to become a valued member of our team. We are seeking an experienced Scientist who combines superb technical, research, analytical and leadership capabilities with a demonstrated ability to get the right things done quickly and effectively. This person must be comfortable working with a team of top-notch developers and collaborating with our research teams. We’re looking for someone who innovates, and loves solving hard problems. You will be expected to have an established background in building highly scalable systems and system design, excellent project management skills, great communication skills, and a motivation to achieve results in a fast-paced environment. You should be somebody who enjoys working on complex problems, is customer-centric, and feels strongly about building good software as well as making that software achieve its operational goals.
Senior Applied Scientist , Buyer Risk Prevention (BRP)
IN, KA, Bengaluru
Do you want to lead the development of advanced machine learning systems that protect millions of customers and power a trusted global eCommerce experience? Are you passionate about modeling terabytes of data, solving highly ambiguous fraud and risk challenges, and driving step-change improvements through scientific innovation? If so, the Amazon Buyer Risk Prevention (BRP) Machine Learning team may be the right place for you. We are seeking a Senior Applied Scientist to define and drive the scientific direction of large-scale risk management systems that safeguard millions of transactions every day. In this role, you will lead the design and deployment of advanced machine learning solutions, influence cross-team technical strategy, and leverage emerging technologies—including Generative AI and LLMs—to build next-generation risk prevention platforms. Key job responsibilities Lead the end-to-end scientific strategy for large-scale fraud and risk modeling initiatives Define problem statements, success metrics, and long-term modeling roadmaps in partnership with business and engineering leaders Design, develop, and deploy highly scalable machine learning systems in real-time production environments Drive innovation using advanced ML, deep learning, and GenAI/LLM technologies to automate and transform risk evaluation Influence system architecture and partner with engineering teams to ensure robust, scalable implementations Establish best practices for experimentation, model validation, monitoring, and lifecycle management Mentor and raise the technical bar for junior scientists through reviews, technical guidance, and thought leadership Communicate complex scientific insights clearly to senior leadership and cross-functional stakeholders Identify emerging scientific trends and translate them into impactful production solutions
Applied Scientist, Artificial General Intelligence, AGI Data Services
US, MA, Boston
The Artificial General Intelligence (AGI) team is seeking a dedicated, skilled, and innovative Applied Scientist with a robust background in machine learning, statistics, quality assurance, auditing methodologies, and automated evaluation systems to ensure the highest standards of data quality, to build industry-leading technology with Large Language Models (LLMs) and multimodal systems. Key job responsibilities As part of the AGI team, an Applied Scientist will collaborate closely with core scientist team developing Amazon Nova models. They will lead the development of comprehensive quality strategies and auditing frameworks that safeguard the integrity of data collection workflows. This includes designing auditing strategies with detailed SOPs, quality metrics, and sampling methodologies that help Nova improve performances on benchmarks. The Applied Scientist will perform expert-level manual audits, conduct meta-audits to evaluate auditor performance, and provide targeted coaching to uplift overall quality capabilities. A critical aspect of this role involves developing and maintaining LLM-as-a-Judge systems, including designing judge architectures, creating evaluation rubrics, and building machine learning models for automated quality assessment. The Applied Scientist will also set up the configuration of data collection workflows and communicate quality feedback to stakeholders. An Applied Scientist will also have a direct impact on enhancing customer experiences through high-quality training and evaluation data that powers state-of-the-art LLM products and services. A day in the life An Applied Scientist with the AGI team will support quality solution design, conduct root cause analysis on data quality issues, research new auditing methodologies, and find innovative ways of optimizing data quality while setting examples for the team on quality assurance best practices and standards. Besides theoretical analysis and quality framework development, an Applied Scientist will also work closely with talented engineers, domain experts, and vendor teams to put quality strategies and automated judging systems into practice.
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