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AWS AI call for proposals — Fall 2024

Advancing the frontiers of machine learning.

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About this CFP

AWS offers a broad and deep set of tools for businesses to create impactful machine learning solutions faster. Our mission is to share our learnings and ML capabilities as fully managed services, and put them into the hands of every scientist and developer.

AWS AI aims to advance machine learning research by funding development of open-source tools and research that benefit the machine learning community at large, or impactful research that uses machine learning tools.

We welcome proposals related to machine learning in the areas below:

  1. Generative AI
  2. Governance and responsible AI
  3. Distributed training
  4. Machine learning compilers and compiler based optimizations

Other applied machine learning topics are also welcome.

Timeline

Submission period: September 25, 2024 - November 13, 2024 (11:59PM Pacific Time)

Decision letters will be sent out February 2025

Award details

Selected Principal Investigators (PIs) may receive the following:

  • Unrestricted funds, no more than $70,000 USD on average
  • AWS Promotional Credits, no more than $50,000 USD on average
  • Training resources, including AWS tutorials and hands-on sessions with Amazon scientists and engineers

Amazon Research Awards (ARA) are structured as one-year unrestricted gifts. 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.

Eligibility requirements

Please refer to the ARA Program rules on the Rules and Eligibility page.

Proposal requirements

Proposals for this CFP should be prepared according to the proposal template and are encouraged to be a maximum of 5 pages, not including Appendices. In addition, to submit a proposal for this CFP, please also include the following information:

  1. Please list the open-source tools you plan to contribute to.
  2. Please list the AWS ML tools you will use.

Selection criteria

ARA will make the funding decisions based on the potential impact to the research community, quality of the scientific content. We encourage research that uses machine learning tools, for example AWS AI/ML services (Amazon SageMaker, Amazon AI services, Amazon Bedrock).

Expectations from recipients

To the extent deemed reasonable, Award recipients should acknowledge the support from ARA. Award recipients will inform ARA of publications, presentations, code and data releases, blogs/social media posts, and other speaking engagements referencing the results of the supported research or the Award. Award recipients are expected to provide updates and feedback to ARA via surveys or reports on the status of their research. Award recipients will have an opportunity to work with ARA on an informational statement about the awarded project that may be used to generate visibility for their institutions and ARA.

How to apply
When you're ready to submit your proposal, use the button below and follow the instructions on the site.
Submit your proposal

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Applied Scientist, Amazon Robotics
US, WA, Seattle
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Applied Scientist , Customer Engagement Technology
US, CA, East Palo Alto
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Research Scientist II, Amazon Dash Cart
US, MA, Boston
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US, WA, Seattle
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Applied Scientist II, FAR (Frontier AI & Robotics)
US, WA, Seattle
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Data Scientist - II, Alexa Sensitive Content Intelligence
IN, KA, Bengaluru
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Senior Applied Scientist, AWS Marketplace & Partner Services
US, WA, Seattle
The AWS Marketplace & Partner Services Science team is hiring an Applied Scientist to develop state-of-the-art recommendations systems, Conversational AI agents, and personalization capabilities within AWS Marketplace. This role will revolutionize discovery of solutions that accelerate customer cloud migrations for our customers, bringing personalization to AWS customers. The ideal candidate is comfortable leading production level recommendations strategies, implementing agent based conversationalAI experience, and mentoring other scientists on the team. You able to evaluate feasibility of scientific approaches and influence business leaders to develop the best experience for our customers. You thrive in a collaborative environment, where mentorship, learning, and teamwork is critical. Key job responsibilities - Work with customers, product managers, scientists, and engineers to deliver production level recommendation experiences - Ability to write production level code and support requirements for MLOps/LLMOps - Mentor Scientists on the team, and guide scientific approach across the organization About the team The AWS Marketplace & Partner Services Science team supports science models and recommendations that are deployed directly to AWS Customers (via AWS Marketplace), to our partners (via Partner Central), and to our internal AWS Sellers. Our mission is to accelerate cloud migrations and modernizations, supporting AWS customers to innovate, and the growth of our AWS Partners.
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