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ARA Program Rules

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Last updated: March 12, 2021

By applying to or participating in the Amazon Research Awards Program (“ARA Program”), you agree to the following rules (“Rules”). These Rules are solely between Amazon Web Services, Inc. (“AWS,” “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 Customer Agreement. The Principal Investigator is 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 their respective 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 or its affiliates within the 12 months preceding application to the ARA Program (“Ineligible Personnel”);

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

(e) has not participated in or had decision-making authority over any cloud infrastructure procurements involving AWS or its affiliates; and

The ARA Program is void in Cuba, Iran, Syria, North Korea, Sudan, the region of Crimea, and where otherwise prohibited by law.

Amazon employees are not eligible to receive an Award.

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 original work;

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

(c) does not 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, AWS Promotional Credit, 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 AWS in its sole discretion. Any cash component of an Award:

(a) will be structured as a one-year 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 incurred solely for your Principal Investigator’s research.

You or your academic institution are responsible for any costs and expenses associated with an Award, including overhead or indirect costs. You will be required to complete administrative requirements to process any cash Award, which may include submitting a W-9 form, completing a tax questionnaire, and registering in Amazon’s Payee Central System. If your organization is unable to complete these requirements in a timely manner, AWS reserves the right to rescind the Award. Any payment from AWS 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 your local tax authorities. These Rules, the agreements referenced herein, and any other agreement regarding the relationship between you and AWS will constitute a Master Agreement under the terms of the purchase order.

IV. AWS Customer Agreement

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.

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 ARA Program and verifying applicant’s 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 Services, Inc., 410 Terry Ave North, Seattle, Washington 98109, USA.

VI. Marketing & Publicity

Except where prohibited, you consent to our use of your name, likeness, biographical information, and voice in advertising, publicity, trade, and other marketing and promotional materials (including video, audio, and print through all means of distribution) worldwide without compensation, notice or approval, and you disclaim any ownership rights to the content of such materials.

You may acknowledge our support by stating that your research is supported by the ARA Program. Any use of the AWS logo is subject to the AWS Trademark Guidelines. Any other use of Amazon logos requires Amazon’s prior written consent. You must receive AWS’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

YOU ACCEPT THE CONDITIONS STATED IN THESE OFFICIAL RULES, AGREES TO BE BOUND BY THE DECISIONS OF AMAZON, AND WARRANT THAT YOU ARE ELIGIBLE TO PARTICIPATE IN THE ARA PROGRAM. 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 RISING 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 OFFICIAL 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 Customer Agreement.

X. Representations and Warranties

You represent and warrant that:

(a) your receipt of any Award is neither prohibited 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 create a conflict of interest for AWS or its affiliates;

(d) you are not participating in, nor have any decision-making authority over, any procurements or purchasing decisions involving AWS or its affiliates on behalf of your organization; 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 and any Award your organization receives will be voidable.

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IN, KA, Bangalore
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Applied Scientist II, Content Experience
IN, KA, Bangalore
Are you interested in changing the Digital Reading Experience? We are from Kindle Books Team looking for a set of Scientists to take the reading experience in Kindle to next level with a set of innovations! We envision Kindle as the place where readers find the best manifestation of all written content optimized with features that enable them to get the most out of reading, and creators are able to realize their vision to customers quickly and at scale. Every time customers open their content, regardless of surface, they start or restart their reading in a familiar, useful and engaging place. We achieve this by building a strong foundation of core experiences and act as a force multiplier and partner for content creators (directly or indirectly) to easily innovate on top of Kindle's purpose built content experience stack in a simple and extensible way. We will achieve this by providing a best-in-class reading experience, unique content experiences, and remaining agile in meeting the evolving needs and preferences of our users. Our goal is to foster long-lasting reading habits and make us the preferred destination for enriching literary experiences. We are building a In The Book Science team and looking for Scientists, who are passionate about Reading and are willing to take Reading to the next level. Every Book is a complex structure with different entities, layout, format and semantics, with more than 17MM eBooks in our catalog. We are looking for experts in all domains like core NLP, Generative AI, CV and Deep Learning Techniques for unlocking capabilities like analysis, enhancement, curation, moderation, translation, transformation and generation in Books based on Content structure, features, Intent & Synthesis. Scientists will focus on Inside the book content and semantically learn the different entities to enhance the Reading experience overall (Kindle & beyond). They have an opportunity to influence in 2 major phases of life-cycle - Publishing (Creation of Books process) and Reading experience (building engaging features & representation in the book thereby driving reading engagement). Key job responsibilities - 3+ years of building machine learning models for business application experience - PhD, or Master's degree and 2+ years of applied research experience - Knowledge of programming languages such as C/C++, Python, Java or Perl - Experience programming in Java, C++, Python or related language - You have expertise in one of the applied science disciplines, such as machine learning, natural language processing, computer vision, Deep learning - You are able to use reasonable assumptions, data, and customer requirements to solve problems. - You initiate the design, development, execution, and implementation of smaller components with input and guidance from team members. - You work with SDEs to deliver solutions into production to benefit customers or an area of the business. - You assume responsibility for the code in your components. You write secure, stable, testable, maintainable code with minimal defects. - You understand basic data structures, algorithms, model evaluation techniques, performance, and optimality tradeoffs. - You follow engineering and scientific method best practices. You get your designs, models, and code reviewed. You test your code and models thoroughly - You participate in team design, scoping and prioritization discussions. You are able to map a business goal to a scientific problem and map business metrics to technical metrics. - You invent, refine and develop your solutions to ensure they are meeting customer needs and team goals. You keep current with research trends in your area of expertise and scrutinize your results. A day in the life You will be working with a group of talented scientists on researching algorithm and running experiments to test solutions to improve our experience. This will involve collaboration with partner teams including engineering, PMs, data annotators, and other scientists to discuss data quality, model development and productionizing the same. You will mentor other scientists, review and guide their work, help develop roadmaps for the team. We are open to hiring candidates to work out of one of the following locations: Bangalore, IND | Bangalore, KA, IND
Director Applied Science, Global Talent Management & Compensation (GTMC)
US, WA, Seattle
Amazon is looking for a strategic, innovative science leader within the Global Talent and Compensation (GTMC) organization to lead an interdisciplinary team charged with developing data-driven solutions to model, automate, and inform high judgement decision making by bringing together science and technology in consumer grade internal talent products. GTMC delivers employee-focused experiences by providing scalable and responsive mechanisms for employees, as well as listening and signaling mechanisms for managers and leaders. They do this through intelligent, flexible, and extensible products and scalable data and science services. They set out to deliver a singular experience supporting multiple employee talent journeys (e.g., onboarding, evaluation, compensation, movement, promotion, exit), to generate and capture signals from product data, surface outliers, increase personalization, and improve the efficacy of “next best action” recommendations, for 1.6 million Amazonians around the world. In this role you will lead multiple research teams across the disciplines of Talent Management, Diversity Equity and Inclusion, and Compensation. You will interface with the most senior leaders at Amazon to develop and deliver on a strategic research roadmap that crosses all lines of Amazon businesses (e.g., Consumer, AWS, Devices, Advertising). This role will then partner with engineering and product management leader to deliver the outcomes of this research in production environments. Successful candidates will have an established background expertise in machine learning with some experience in applying this expertise to the fields of talent management, product management and/or software development. We are open to hiring candidates to work out of one of the following locations: Seattle, WA, USA
Sr. Applied Scientist
US, WA, Seattle
Are you interested in building, developing, and driving the machine learning technical vision, strategy, and implementation for AWS Hardware? AWS Hardware is hiring a Senior Applied Scientist (AS) to lead the definition and prioritization of our customer focused technologies and services. AWS Hardware is responsible for designing, qualifying, and maintaining server solutions for AWS and its customers as well as developing new cloud focused hardware solutions. You will be a senior technical leader in the existing Data Sciences and Analytics Team, build, and drive the data science and machine learning needed for our product development and operations. As a Senior AS at Amazon, you will provide technical leadership to the teams, organization and products for machine learning. Senior AS’s are specialists with deep expertise in areas such as machine learning, speech recognition, large language models (LLMs), natural language processing, computer vision, and knowledge acquisition, and help drive the ML vision for our products. They are externally aware of the state-of-the-art in their respective field of expertise and are constantly focused on advancing the state-of-the-art for improving Amazon’s products and services. The ideal candidate will be an expert in the areas of data science, machine learning, and statistics; specifically in recommendation systems development, classification, and LLMs. You will have hands-on experience leading multiple simultaneous product development and operations initiatives as well as be able to balance technical leadership with strong business judgment to make the right decisions about technology, infrastructure, methodologies, and productionizing models and code. You will strive for simplicity, and demonstrate significant creativity and high judgment backed by statistical proof. Key job responsibilities MS in Data Science, Machine Learning, Statistics, Computer Science, Applied Math or equivalent highly technical field. 10+ years of hands-on experience working in data science and/or machine learning using models and methods such as neural networks, random forests, SVMs or Bayesian classification. 3+ years developing recommendation systems and/or LLMs. 3+ years of experience working in software development, machine learning engineering or ops. Have a history of building highly scalable systems that capture and utilize large data sets in order to quantify your products performance via metrics, monitoring, and alarming. Experience using R, Python, Java, or other equivalent statistics and machine learning tools. Experienced in computer science fundamentals such as object-oriented design, data structures and algorithm design. 3+ years of experience developing in a cloud environment. We are open to hiring candidates to work out of one of the following locations: Seattle, WA, USA
Applied Scientist
US, WA, Seattle
Are you a scientist interested in pushing the state of the art in LLMs, ML or Computer Vision forward? Are you interested in working on ground-breaking research projects that will lead to great products and scientific publications? Do you wish you had access to large datasets? Answer yes to any of these questions and you’ll fit right in here at Amazon. We are looking for a hands-on researcher, who wants to derive, implement, and test the next generation of Generative AI algorithms (either LLMs, Diffusion Models, auto-regressors, VAEs, or other generative models). The research we do is innovative, multidisciplinary, and far-reaching. We aim to define, deploy, and publish cutting edge research. In order to achieve our vision, we think big and tackle technology problems that are cutting edge. Where technology does not exist, we will build it. Where it exists we will need to modify it to make it work at Amazon scale. We need members who are passionate and willing to learn. “Amazon Science gives you insight into the company’s approach to customer-obsessed scientific innovation. Amazon fundamentally believes that scientific innovation is essential to being the most customer-centric company in the world. It’s the company’s ability to have an impact at scale that allows us to attract some of the brightest minds in artificial intelligence and related fields. Our scientists continue to publish, teach, and engage with the academic community, in addition to utilizing our working backwards method to enrich the way we live and work.” Please visit https://www.amazon.science for more information #hltech #hitech Key job responsibilities - Derive novel ML or Computer Vision or LLMs and NLP algorithms - Design and develop scalable ML solutions - Work with very large datasets - Work closely with software engineering teams and Product Managers to deploy your innovations - Publish your work at major conferences/journals. - Mentor team members in the use of your Generative AI and LLMs. About the team We are a tight-knit group that shares our experiences and help each other succeed. We believe in team work. We love hard problems and like to move fast in a growing and changing environment. We use data to guide our decisions and we always push the technology and process boundaries of what is feasible on behalf of our customers. If that sounds like an environment you like, join us. We are open to hiring candidates to work out of one of the following locations: Seattle, WA, USA
Applied Scientist, AGI - Intelligent Decisions
GB, Cambridge
The Artificial General Intelligence team (AGI) has an exciting position for an Applied Scientist with a strong background NLP and Large Language Models to help us develop state-of-the-art conversational systems. As part of this team, you will collaborate with talented scientists and software engineers to enable conversational assistants capabilities to support the use of external tools and sources of information, and develop novel reasoning capabilities to revolutionise the user experience for millions of Alexa customers. Key job responsibilities As an Applied Scientist, you will develop innovative solutions to complex problems to extend the functionalities of conversational assistants . You will use your technical expertise to research and implement novel algorithms and modelling solutions in collaboration with other scientists and engineers. You will analyse customer behaviours and define metrics to enable the identification of actionable insights and measure improvements in customer experience. You will communicate results and insights to both technical and non-technical audiences through written reports, presentations and external publications. We are open to hiring candidates to work out of one of the following locations: Cambridge, GBR | London, GBR
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