Frequently asked questions

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In addition to the FAQs below, please view the ARA Program Rules.

General program 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. ARA aims to fund projects leading toward a PhD degree or conducted as a part of post-doctoral work.

Is the AWS Machine Learning Research Awards (MLRA) program part of ARA?
Yes, in 2020 the two programs merged and MLRA now funds awards through ARA, under the AWS AI call for proposal.

What is the structure of an ARA award? Can it be extended?
Awards are structured as one-year 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.

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, and more. Please refer to the detailed CFPs for more information.

Applying for an award

Who is eligible to apply?
Researchers from around the world are encouraged to apply. Please refer to the ARA Program Rules for eligibility.

How do I apply?
Please follow the instructions on the specific CFP you are applying to.

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 should be submitted by a single faculty member, who will also supervise the student or post-doc who is to be funded by the award. Other members of the research team can and should be mentioned in the proposal.

Is it possible for one faculty member to be on multiple grants?
Principle Investigators can only submit one proposal at each deadline. Your proposal can be considered for a second CFP with the same deadline, if it meets the scope of both CFPs. Please follow the instructions when you are submitting your proposal.

What budget expenses will Amazon consider for the award?
A proposed cash budget is generally expected to support one or two PhD 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 should not 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.

Proposal review process

Who will evaluate the proposals and when will I know the outcome of the review?
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.

Additional information

May I speak to someone from the Amazon Research Awards team to find out more?
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.

Can I be added to upcoming CFP announcements?
Yes, please email research-awards@amazon.com to be added to the quarterly CFP email announcement.

Are there any other funding opportunities offered by Amazon?
Yes, please visit the Academic Engagements page for more information. Note that the AWS Machine Learning Research Awards program is part of ARA.

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.

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Applied Scientist
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Are you excited about driving business growth for millions of sellers through application of Machine Learning and other advanced computer science disciplines? Do you thrive in a fast-moving, large-scale environment that values data-driven decision making and sound scientific practices? We are looking for experienced applied scientists build the next level of intelligence that will help Amazon Marketplace Sellers to succeed and grow their businesses.Amazon Marketplace enables sellers to put their products in front of hundreds of millions of customers and offers sellers the tools and services needed to make e-commerce successful, efficient and simple. Our team is responsible for building the core intelligence, insights, and algorithms that support a broad range of products and features that Amazon Marketplace Sellers depend on. We are tackling large-scale, challenging problems such as helping sellers to prioritize business tasks, and predicting customer demand for new products, by bringing together petabytes of data from diverse sources across Amazon.You should have a proven track-record of delivering solutions using advanced computer science approaches. You will be comfortable using a variety of tools and data sources to answer high-impact business questions that impact millions of customers globally, and be able to break down complex information and insights into clear and concise language and be comfortable presenting your findings to audiences with a broad range of backgrounds.Responsibilities:Develop production software systems utilizing advanced algorithms to solve business problems.Analyze and validate data using data, algorithms, and statistical tools to ensure high data quality and reliable insights.Proactively identify interesting areas for deep dive investigations and future product development.Design and execute experiments, and analyze experimental results in collaboration with Product Managers, Business Analysts, Economists, and other specialists.Partner with data engineering teams across multiple business lines to improve data assets, quality, metrics and insights.Leverage industry best practices to establish repeatable applied science practices, principles & processes.*scijobsAmazon is an Equal Opportunity-Affirmative Action Employer – Minority / Female / Disability / Veteran / Gender Identity / Sexual Orientation.
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US, WA, Seattle
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Data Scientist II - AMZ4743
US, WA, Seattle
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Applied Scientist
US, WA, Seattle
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Sr. Applied Scientist, Alexa AI
US, CA, San Diego
Do you want to join Alexa AI -- the science team behind Amazon’s intelligence voice assistance system? Do you want to utilize cutting-edge deep-learning and machine learning algorithms to delight millions of Alexa users around the world?If your answers to these questions are “yes”, then come join the Alexa Artificial Intelligence team. We are responsible for the deep learning technology that is central to the automated ranking and arbitration to optimize for end-to-end customer satisfaction.As an Senior Applied Scientist you will work with talented peers to develop novel algorithms and modeling techniques to advance the state of the art in spoken language understanding. Your work will directly impact our customers in the form of products and services that make use of speech and language technology. You will leverage Amazon’s heterogeneous data sources and large-scale computing resources to accelerate advances in spoken language understanding.
Applied Scientist
US, WA, Seattle
#FoundItOnAmazon is to be an upper funnel browsing experience designed to show customers an endless stream of inspirational products. It is a companion to Amazon's search experience and is meant to drive habitual interaction on Amazon and lead to serendipitous purchases. It is deliberately diverse, visually engaging, and meant to encourage customers to experience the thrill of the hunt. Our vision is for #FoundItOnAmazon to be the first destination for customers to find inspiration and drive customers to visit Amazon more often. #FoundItOnAmazon provides inspiration that converts to purchases, and collects engagement signals (follow, hearts) that can improve the customer’s experience across Amazon.The team is looking for an Applied Scientist to be based in Seattle area. As a key member of the team, you will provide machine learning expertise that helps accelerate the business. You will build various data and machine learning models that help us innovate different ways to enhance the customer experience. You will need to be entrepreneurial, wear many hats, and work in a highly collaborative environment. We like to move fast, experiment, iterate and then scale quickly, thoughtfully balancing speed and quality.An ideal candidate will be an expert in the areas of machine learning and statistics who will have expertise in applying theoretical models in an applied environment. The candidate will be expected to work on numerous aspects of Machine Learning such as feature engineering, predictive modeling, probabilistic modeling, hyper-parameter tuning, scalable inference methods and latent variable models including transfer learning. Challenges will involve dealing with very large data sets and requirements on throughput.Responsibilities include:· Design, implement, test, deploy, and maintain innovative data and machine learning solutions to accelerate our business.· Create experiments and prototype implementations of new learning algorithms and prediction techniques· Collaborate with scientists, engineers, product managers, and stockholders to design and implement software solutions for science problems· Use machine learning best practices to ensure a high standard of quality for all of the team deliverables
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