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Foundation Model Development call for proposals — Winter 2024

Advancing the frontiers of foundation model development.

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About this CFP

AWS offers a broad and deep set of services for organizations to create meaningful 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 is soliciting funding proposals related to foundation model (FM) development, including enhancements for dialogue, factual questioning and answering, text generation, document summarization, image generation, and more. Proposals should be expanding the state of the art in terms of training methods, with a focus on one of the following areas: 1) to reduce incorrect or nonsensical answers, 2) to reduce the sensitivity to tweaks to the input prompt, 3) ask clarifying questions when facing ambiguous questions, 4) develop efficiency enhancements across the training and hosting FM lifecycle.

We are inviting work that both critiques and enhances the state-of-the-art in FM, including but not limited to the following topics:

  • Reinforcement learning with human feedback
  • Scaling laws and their inverse, including for model fine-tuning
  • Novel datasets and training methods
  • Distillation with enhanced reasoning
  • Foundation models in novel modalities and domains, such as biology, manufacturing, fashion, etc.
  • Bias detection and mitigation throughout the foundation model lifecycle

AWS aims to advance foundation model development by funding the creation of open-source artifacts, datasets and code that benefit the research community at large, or impactful research that uses machine learning tools. AWS will provide credits for use on EC2 instances powered by AWS Trainium chips to help researchers develop and test solutions at scale. In addition to AWS Trainium, proposed research can be conducted using AWS AI Services, AWS ML Services (Amazon SageMaker, Amazon SageMaker Ground Truth, Amazon SageMaker Neo, and Amazon Augmented AI), and Amazon Bedrock.

Timeline

  • Submission period: January 17 - March 6, 2024 (11:59PM Pacific Time)
  • Decision letters will be sent out in October 2024

Award details

Selected Principal Investigators (PIs) may receive the following:

  • $250,000 in AWS Promotional Credits, which can be used on generally available EC2 instances that are powered by AWS Trainium chips
  • AWS Trainium training resources, including AWS tutorials and hands-on sessions with Amazon scientists and engineers

Awards 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.

Your receipt and use of AWS Promotional Credits is governed by the AWS Promotional Credit Terms and Conditions, which may be updated by AWS from time to time.

Eligibility requirements

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

Proposal requirements

PIs are encouraged to exemplify how their proposed techniques or research studies expand the body of knowledge on pretraining and evaluation methods. PIs should either include plans for open source contributions or state that they do not plan to make any open source contributions (data or code) under the proposed effort. 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.

Selection criteria

Funding decisions are based on the creativity and quality of the scientific content, and potential impact to the research community and society at large. AWS may solicit feedback on proposal title and abstracts from select AWS customers, but final award decisions will be made solely by AWS. Proposals will be evaluated based on their express interest in open-sourcing their model artifacts, datasets, and development frameworks. Although usage of Trainium is not a requirement, proposals will be evaluated on their intention to use and explore novel hardware for AI/ML, such as Trainium.

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 engage with AWS throughout the duration of their award year including, but not limited to, providing reports on the status of their research or updates and feedback to ARA via surveys. Award recipients will have the 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.

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Principal Economist, Ads Econ
US, WA, Seattle
Amazon Advertising is one of Amazon's fastest growing and most profitable businesses. Our products are used daily to surface new selection and provide customers a wider set of product choices along their shopping journeys. The business is focused on generating value for shoppers as well as advertisers. Our team uses a combination of econometrics, machine learning, and data science to build disruptive products for all our Advertising products. We also generate insights to guide Amazon Advertising strategy, providing direct support to senior leadership. We are looking for an experienced Economist who have a deep passion for building state-of-art causal models and ads measurement and optimization solutions, ability to communicate data insights and scientific vision, and execute strategic projects. As an Economist on this team, you will: - Lead the design and analysis of large-scale experiments to measure advertising effectiveness across Amazon's advertising products - Develop novel causal inference and econometric methodologies to solve attribution and incrementality measurement challenges at scale - Invent new optimization frameworks that translate measurement insights into actionable bidding, targeting, and budget allocation strategies for advertisers - Define the long-term science roadmap for ads measurement and optimization, identifying high-impact research directions and driving alignment across engineering, product, and science teams - Build and refine structural and reduced-form models that quantify the causal impact of advertising on consumer behavior, sales, and brand outcomes - Partner with engineering teams to operationalize econometric models into production systems serving millions of advertisers - Mentor and develop a team of economists and applied scientists, raising the bar on methodological rigor and scientific impact - Influence senior leadership through clear communication of complex economic concepts, shaping investment decisions and product strategy - Collaborate cross-functionally with product managers, engineers, and business leaders to translate business problems into well-defined economic questions with scalable solutions Why you will love this opportunity: Amazon is investing heavily in building a world-class advertising business. This team defines and delivers a collection of advertising products that drive discovery and sales. Our solutions generate billions in revenue and drive long-term growth for Amazon’s Retail and Marketplace businesses. We deliver billions of ad impressions, millions of clicks daily, and break fresh ground to create world-class products. We are a highly motivated, collaborative, and fun-loving team with an entrepreneurial spirit - with a broad mandate to experiment and innovate. Impact and Career Growth: You will invent new experiences and influence customer-facing shopping experiences to help suppliers grow their retail business and the auction dynamics that leverage native advertising; this is your opportunity to work within the fastest-growing businesses across all of Amazon! Define a long-term science vision for our advertising business, driven from our customers' needs, translating that direction into specific plans for research and applied scientists, as well as engineering and product teams. This role combines science leadership, organizational ability, technical strength, product focus, and business understanding.
Principal Data Scientist, Prime Video
US, WA, Seattle
Interested in influencing what customers around the world see when they turn on Prime Video? The Prime Video Personalization and Discovery team matches customers with the right content at the right time, at all touch points throughout the content discovery journey. We are looking for a customer-focused, solutions-oriented Principal Data Scientist to develop next-gen measurement and experimentation systems within Prime Video Personalization and Discovery. You'll be part of an embedded science team driving projects across product and engineering teams that ultimately influence what millions of customers around the world see when the log into Prime Video. The ideal candidate brings experience building experiment-based measurement systems at scale, excellent stakeholder communication skills, and the ability to balance technical rigor with delivery speed and customer impact. You will build cross-functional support within Prime Video for high-quality, rigorous measurement, assess business problems, and support iterative scientific solutions that balance short-term delivery with long-term science roadmaps. Key job responsibilities - Define and drive the multi-year vision for experiment-based measurement systems within Prime Video - Partner with product stakeholders and science peers to identify strategic data-driven opportunities to improve the customer experience - Communicate findings, conclusions, and recommendations to technical and non-technical business leaders across Prime Video - Educate senior leaders about and advocate for high-quality measurement as an input to data-driven decisions - Mentor junior scientists and review technical artifacts to ensure quality - Stay up-to-date on the latest data science tools, techniques, and best practices and help evangelize them across the organization
Research Scientist, WWGS Real Estate & Store Development
US, WA, Seattle
Do you want to help shape the future of Amazon's physical retail presence? Worldwide Grocery Stores (WWGS), Location Strategy and Analytics team is looking for an Research Scientist to join us in developing advanced forecasting models, optimization models, and analytical tools to support critical real estate and store planning decisions for Amazon's Worldwide Grocery business, including Whole Foods Market. Our team is responsible for developing predictive models and tools to support Real Estate and Topology analysts in making important decisions regarding our stores—including new store openings, relocations, closures, remodels, design, new formats, and more. We leverage statistical modeling, machine learning, and GenAI to build solutions for store sales forecasting, sales transfer effects, macrospace optimization, store network optimization, store network diffusion planning, and causal effects. As a Research Scientist on our team, you will apply your technical and analytical skills to tackle complex business problems and develop innovative solutions to improve our forecasting and decision-making capabilities. You will collaborate with a diverse team of scientists, economists, and business partners to identify opportunities, develop hypotheses, build internal products, and translate analytical insights into actionable recommendations for Executive Leadership. Key job responsibilities - Design and implement forecasting models and machine learning solutions to predict store performance and optimize our retail network. - Analyze large datasets to uncover insights and patterns related to store performance, customer behavior, and market dynamics. - Develop end-to-end solutions, tools and frameworks to scale our ML model development and data analysis. - Leverage GenAI models to enhance user interaction with our solutions, improve overall user experience, and build new features. - Present research findings and recommendations to scientists, business leaders, and executives. - Collaborate with cross-functional teams to drive adoption of models and insights. - Stay current on latest developments in relevant fields and propose innovative approaches. About the team We are a team of scientists passionate about leveraging data and advanced analytics to drive strategic decisions for Amazon's grocery business. Our work directly impacts Amazon's worldwide grocery store growth and development strategy. We foster a collaborative environment where team members are encouraged to think creatively, challenge assumptions, and pursue novel approaches to solving complex problems. Our team is at the forefront of applying a multitude of techniques - including GenAI - to improve our scientific solutions and products.
Applied Scientist, Customer Behavior Analytics
US, WA, Seattle
The Customer Behavior Analytics team designs innovative machine learning solutions to enhance customer experiences and strengthen their relationship with Amazon. This interdisciplinary team of scientists and engineers incubates and develops disruptive solutions using state-of-the-art technology to tackle some of the most challenging scientific problems in customer behavior analysis at Amazon. To achieve this, the team utilizes methods from deep learning, large language models (LLMs), natural language models, recommendation systems, affinity models, reinforcement learning, and econometrics to drive personalized experiences throughout the customer journey. As a Customer Behavior Analytics Scientist, you will have the opportunity to make a significant business impact, delve into large-scale problems, drive measurable actions, and collaborate closely with other scientists and engineers. You will be responsible for designing and developing state-of-the-art models and working with business, marketing, and engineering teams to address key challenges in customer behavior analytics. Key responsibilities include: - Design and fine-tune language and generative models for recommendation and engagement, including continued pre-training, supervised fine-tuning, and preference-based alignment, to optimize for long-term customer value rather than short-term clicks. - Develop generative recommendation and decision models that produce next-best customer engagement actions (e.g., recommendations, bundles, messaging, incentives, timing), conditioned on structured customer and household-level behavioral context. - Build structured, temporal representations of customer behavior (e.g., lifecycle stage, needs, replenishment patterns, engagement history) and integrate them into generative and deep learning models to enable long-horizon reasoning. - Experiment scalable representations of customer and household behavior that summarize long engagement history into compact states, supporting efficient, incremental inference in large-scale inference. - Design and apply post-training optimization techniques (e.g., auxiliary objectives, preference modeling, offline reinforcement learning or policy optimization) to align model behavior with long-term engagement, satisfaction, and retention metrics. - Develop robust evaluation frameworks combining offline metrics, counterfactual analysis, and online experimentation to measure both immediate impact and long-term customer outcomes. In this role, you will be an analytical problem solver who enjoys exploring data, participating in problem-solving efforts, developing new frameworks, and engaging in investigations and algorithm development. You should be capable of effectively collaborating with technical teams and business stakeholders, pushing the boundaries of what is scientifically possible, and maintaining a sharp focus on measurable customer satisfaction and business impact. Your work will be crucial in shaping the future of customer behavior analytics at Amazon, driving innovation that directly impacts millions of customers worldwide. This position offers a high-visibility opportunity to contribute to solutions that are vital to improving customer satisfaction and loyalty, serving as a model for customer-centric solutions across the company.
Economist, People Experience and Technology Central Science
US, WA, Seattle
PXTCS is looking for an economist who can apply economic methods to address business problems. The ideal candidate will work with engineers and computer scientists to estimate models and algorithms on large scale data, design pilots and measure impact, and transform successful prototypes into improved policies and programs at scale. PXTCS is looking for creative thinkers who can combine a strong technical economic toolbox with a desire to learn from other disciplines, and who know how to execute and deliver on big ideas as part of an interdisciplinary technical team. Key job responsibilities * Ideal candidates will work in a team setting with individuals from diverse disciplines and backgrounds. * They will work with teammates to develop scientific models and conduct the data analysis, modeling, and experimentation that is necessary for estimating and validating models. * They will work closely with engineering teams to develop scalable data resources to support rapid insights, and take successful models and findings into production as new products and services. * They will be customer-centric and will communicate scientific approaches and findings to business leaders, listening to and incorporate their feedback, and delivering successful scientific solutions. A day in the life The Economist will work with teammates to apply economic methods to business problems. This might include identifying the appropriate research questions, writing code to implement a DID analysis or estimate a structural model, or writing and presenting a document with findings to business leaders. Our economists also collaborate with partner teams throughout the process, from understanding their challenges, to developing a research agenda that will address those challenges, to help them implement solutions. About the team The People eXperience and Technology Central Science (PXTCS) team uses economics, behavioral science, statistics, and machine learning to proactively identify mechanisms and process improvements which simultaneously improve Amazon and the lives, wellbeing, and the value of work to Amazonians. PXTCS is an interdisciplinary team that combines the talents of science and engineering to develop and deliver solutions that measurably achieve this goal.
Data Scientist II, SCOT OSS - Sourcing Execution & Performance
US, WA, Bellevue
Have you ever ordered a product on Amazon and when that box with the smile arrived, wondered how it got to you so fast? Wondered where it came from and how much it cost Amazon? If so, the Amazon Global Supply Chain Optimization Technology (SCOT) organization is for you. Watch this video to learn more about our organization, SCOT: http://bit.ly/amazon-scot We are the Optimal Sourcing Systems team (OSS) within SCOT and are looking for a Data Scientist II to join us! OSS designs and builds systems that measure and manage Amazon’s supplier capabilities, identify and react to supply disruptions, and prioritizes inbound freight for our global network. OSS software is used by every country Amazon services, and is a critical link to ensuring Amazon offers the products our customers want, at the lowest possible cost. This team under OSS orchestrates and tracks inventory movement into Amazon's network, maintains performance feedback loops, and ensures vendor compliance. The Data Scientist II, in partnership with the Product Management, Operations, and Tech teams, will lead efforts in four areas: 1) Building models to set optimal parameters such as lead times to ensure the accuracy of our Inbound network 2) Building analytical frameworks to identify and drive improvements in purchase order lifecycle management and defect coaching/chargebacks 3) Developing Gen AI solutions related to dispute evaluation and vendor coaching 4) Building models and solutions to enable collaborative inventory planning with vendors The ideal candidate thrives in ambiguous problem spaces, relishes working with large volumes of data, and enjoys the challenge of highly complex supply chain contexts. They can translate complex business logic into scalable models and communicate insights effectively to both technical and non-technical stakeholders. Keys to success in this role include exceptional analytics, statistics, judgment, and communication skills. Experience with supply chain optimization, operations research, or vendor management systems is a plus. Key job responsibilities - Collaborate with product managers, science, and engineering teams to design and implement model solutions for Sourcing Execution & Performance systems - Use large datasets or experiments to make causal inferences or predictions - Work with engineers to automate science analysis processes and build scalable measurement solutions - Interpret data, write reports, and make actionable recommendations - Drive technical standards and best practices for the team's Science solutions - Mentor and provide technical guidance to other team members on complex projects A day in the life Amazon offers a full range of benefits that support you and eligible family members, including domestic partners and their children. Benefits can vary by location, the number of regularly scheduled hours you work, length of employment, and job status such as seasonal or temporary employment. The benefits that generally apply to regular, full-time employees include: - Medical, Dental, and Vision Coverage - Maternity and Parental Leave Options - Paid Time Off (PTO) - 401(k) Plan If you are not sure that every qualification on the list above describes you exactly, we'd still love to hear from you! At Amazon, we value people with unique backgrounds, experiences, and skillsets. If you’re passionate about this role and want to make an impact on a global scale, please apply!
Applied Scientist III - AMZ9898584
US, MA, Boston
MULTIPLE POSITIONS AVAILABLE Employer: AMAZON DEVELOPMENT CENTER U.S., INC. Offered Position: Applied Scientist III Job Location: Boston, Massachusetts Job Number: AMZ9898584 Position Responsibilities: Participate in the design, development, evaluation, deployment and updating of data-driven models and analytical solutions for machine learning (ML) and/or natural language (NL) applications. Develop and/or apply statistical modeling techniques (e.g. Bayesian models and deep neural networks), optimization methods, and other ML techniques to different applications in business and engineering. Routinely build and deploy ML models on available data, and run and analyze experiments in a production environment. Identify new opportunities for research in order to meet business goals. Research and implement novel ML and statistical approaches to add value to the business. Mentor junior engineers and scientists. Position Requirements: Master’s degree or foreign equivalent degree in Computer Science, Machine Learning, Engineering, or a related field and two years of research or work experience in the job offered, or as a Research Scientist, Research Assistant, Software Engineer, or a related occupation. Employer will accept a Bachelor’s degree or foreign equivalent degree in Computer Science, Machine Learning, Engineering, or a related field and five years of progressive post-baccalaureate research or work experience in the job offered or a related occupation as equivalent to the Master’s degree and two years of research or work experience. Must have one year of research or work experience in the following skill(s): (1) programming in Java, C++, Python, or equivalent programming language; and (2) conducting the analysis and development of various supervised and unsupervised machine learning models for moderately complex projects in business, science, or engineering. Amazon.com is an Equal Opportunity-Affirmative Action Employer – Minority / Female / Disability / Veteran / Gender Identity / Sexual Orientation. 40 hours / week, 8:00am-5:00pm, Salary Range $167,100/year to $226,100/year. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, visit: https://www.aboutamazon.com/workplace/employee-benefits.#0000
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