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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 in March 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.
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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
Senior Manager, Applied Science, Prime Video Advertising
US, NY, New York
Prime Video is a first-stop entertainment destination offering customers a vast collection of premium programming in one app available across thousands of devices. Prime members can customize their viewing experience and find their favorite movies, series, documentaries, and live sports – including Amazon MGM Studios-produced series and movies; licensed fan favorites; and programming from Prime Video add-on subscriptions such as Apple TV+, Max, Crunchyroll and MGM+. All customers, regardless of whether they have a Prime membership or not, can rent or buy titles via the Prime Video Store, and can enjoy even more content for free with ads. Are you interested in shaping the future of entertainment and advertising? Prime Video's technology teams are creating best-in-class digital video experiences, and our Advertising Product & Technology organization is at the forefront of revolutionizing the streaming advertising landscape. The Prime Video Advertising team delivers ad tech solutions that power Prime Video's rapidly growing advertising business across video-on-demand (VOD), live streaming, and display ads—delivering value to both advertisers and viewers worldwide. We focus on critical areas including ad delivery, machine learning-driven optimization, experimentation, audience measurement, and generative AI-powered ad creative solutions. We are seeking a Senior Manager, Applied Science to lead a team of scientists and engineers building machine learning and AI solutions that directly impact Prime Video's advertising business. In this role, you will own the science strategy and execution for key workstreams including: - Ad Load Optimization – Balancing advertising revenue with viewer engagement through sophisticated ML models that determine optimal ad frequency, placement, and duration - Yield Optimization – Maximizing advertising revenue through intelligent allocation, pricing, and forecasting models - Experimentation & Metrics – Designing and scaling experimentation frameworks and causal inference methods to measure the impact of advertising decisions on both business outcomes and customer experience - Ad Creative Generation & Augmentation – Leveraging generative AI to create, personalize, and enhance ad creatives at scale As a leader of leaders, you will set the 3-5 year scientific vision for your organization, build and develop a high-performing team of senior scientists and managers, and drive large-scale ML/AI initiatives that inform strategic decisions for one of the world's largest streaming advertising platforms. You will collaborate closely with engineering, product, and business teams to translate complex scientific capabilities into measurable business impact during a period of rapid growth with a path to $10B in advertising revenue. This role offers the unique opportunity to shape the science strategy for a new and fast-growing business, working at the intersection of machine learning, generative AI, causal inference, and advertising technology at Internet scale.
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.
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