AWS Database Services Call for Proposals - Fall 2023

About this CFP

AWS solicits gift-funded research proposals with innovative approaches to designing, building, or operating large-scale database services or distributed cloud services with a strong data management component. Proposals should seek to advance the state-of-the-art in database management and distributed systems in the following topic areas:

  1. Intelligent database services in which machine learning techniques are applied to optimize the configuration or operation of the system, including efficient resource management.
  2. Global database services where data is distributed and replicated in multiple regions of the world while the system ensures consistency, performance, and data sovereignty.
  3. Correct database services whose design and operation includes formal methods, model checking, fuzzing, and other techniques for ensuring that the system performs according to a specification.
  4. Private and secure database services that incorporate homomorphic encryption, secure multi-party protocols, differential privacy, or other techniques to protect data at rest while permitting complex queries.
  5. Real-time database services for predictive analytics where frequently ingested data feeds into continuous queries,

Timeline

Submission period: September 21, 2023 - November 13, 2023 (11:59PM Pacific Time)

Decision letters will be sent out March 2024

Award details

Selected Principal Investigators (PIs) may receive the following:

  • Unrestricted funds, no more than $100,000 USD on average
  • AWS Promotional Credits, no more than $40,000 USD on average
  • 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. 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 should be prepared according to the proposal template. No third parties should be involved in the projects.

Selection criteria

AWS Database Services will make the funding decisions based on the potential impact to the research community and , quality of the scientific content and relevance to Amazon strategic directions.

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.

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We are seeking a Robotics/AI Motor Control Scientist to develop cutting-edge machine learning algorithms for motor control systems in robots. In this role, you will focus on creating and optimizing intelligent motor control strategies to enable robots to perform complex, whole-body tasks. Your contributions will be essential in advancing robotics by enabling fluid, reliable, and safe interactions between robots and their environments. Key job responsibilities - Develop controllers that leverage reinforcement learning, imitation learning, or other advanced AI techniques to achieve natural, robust, and adaptive motor behaviors - Collaborate with multi-disciplinary teams to integrate motor control systems with robotic hardware, ensuring alignment with real-world constraints such as actuator dynamics and energy efficiency - Use simulation and real-world testing to refine and validate control algorithms - Stay updated on advancements in robotics, AI, and control systems to apply advanced techniques to robotic motion challenges - Lead technical projects from conception through production deployment - Mentor junior scientists and engineers - Bridge research initiatives with practical engineering implementation About the team Fauna Robotics, an Amazon company, is building capable, safe, and genuinely delightful robots for everyday life. Our goal is simple: make robots people actually want to live and interact with in everyday human spaces. We believe that future won’t arrive until building for robotics becomes far more accessible. Today, too much effort is spent reinventing the fundamentals. We’re changing that by developing tightly integrated hardware and software systems that make it faster, safer, and more intuitive to create real-world robotic products. Our work spans the full stack: mechanical design, control systems, dynamic modeling, and intelligent software. The focus is not just functionality, but experience. We’re building robots that feel responsive, expressive, and genuinely useful. At Fauna, you’ll work at the frontier of this space, helping define how robots move, manipulate, and interact with people in natural environments. It’s an opportunity to solve hard problems across hardware and software with a team focused on making robotics accessible and joyful to build. If you care about making robotics real for everyone and building systems that are as delightful as they are capable, we’re interested in hearing from you. an opportunity to solve hard problems across hardware and software with a team focused on making robotics accessible and joyful to build. If you care about making robotics real for everyone and building systems that are as delightful as they are capable, we’re interested in hearing from you.
GB, London
Come build the future of entertainment with us. Are you interested in shaping the future of movies and television? Do you want to define the next generation of how and what Amazon customers are watching? Prime Video is a premium streaming service that offers customers a vast collection of TV shows and movies — all with the ease of finding what they love to watch in one place. We offer customers thousands of popular movies and TV shows from Originals and Exclusive content to exciting live sports events. We also offer our members the opportunity to subscribe to add-on channels which they can cancel at anytime and to rent or buy new release movies and TV box sets on the Prime Video Store. Prime Video is a fast-paced, growth business — available in over 240 countries and territories worldwide. The team works in a dynamic environment where innovating on behalf of our customers is at the heart of everything we do. If this sounds exciting to you, please read on. Prime Video Commerce's mission is to present the right offer to the right customer at the right time — across subscriptions, channels, and transactional video in every market and on every device. Our science team replaces static business rules with ML-driven decisions that personalise the entire commerce journey, from discovery through to checkout and beyond. We operate at scale across hundreds of millions of customers, and we are now expanding into new frontiers — combining the latest advances in agentic and generative AI, behavioural simulation, and causal inference to understand the impact of our decisions before they reach customers. We are looking for an Applied Scientist to join the Prime Video Commerce Insights team who will work on the latest research and machine learning to build scalable personalisation solutions. You will develop and deploy customer-facing models, understand customer behaviour at scale, and explore emerging techniques that help us make better decisions faster. This is a hands-on role working with a high performing and high visibility multidisciplinary group of engineers and scientists in the London office, focused on improving the customer experience for Prime Video and the wider Amazon organization. You will contribute to the design of machine learning models that scale to large quantities of data and serve low-latency recommendations to all customers worldwide. You will embody scientific rigor in designing and executing experiments to demonstrate the technical efficacy and business value of your methods. You will work alongside a science and engineering team that embodies the customer obsession principle by developing recommendation and decision systems that raise the profile of Prime Video Commerce as a global leader in machine learning and personalisation. Successful candidates will have strong technical ability, a focus on customers by applying a customer-first approach, and excellent teamwork and communication skills. The position offers exceptional opportunities for every candidate to grow their technical and non-technical skills. Key job responsibilities - Research, design, and implement recommendation systems that personalise across different customer experience touch points. - Collaborate with engineers to deploy and integrate successful model experiment results into large-scale, complex Amazon production systems with low latency. - Provide machine learning thought leadership to both technical and business leaders, with the ability to think strategically about business, product, and technical challenges. - Be a subject matter expert in reinforcement learning approaches for the team and actively contribute to the science roadmap - Define the science roadmap and research agenda that aligns with the organisation's priorities and production constraints. - Work with technical product managers to work backwards from what's important to customers and deliver machine-backed solutions. - Report and share results with the team and wider scientific community by authoring documents that are both statistically rigorous and compellingly relevant, exemplifying good scientific practice in a business environment. A day in the life You will be both a research leader and a hands-on innovator within the Commerce Insights organisation. You'll collaborate with talented engineers and senior leaders to solve problems that are uniquely challenging at Amazon's scale: personalising commerce decisions across multiple business lines balancing competing objectives across offerings, and positively impacting hundreds of millions of customers worldwide. The problems here are technically deep — combining large-scale ML, causal reasoning, and behavioural modelling in a domain where every decision carries real revenue and customer experience consequences. Your research will ship to production and move metrics that matter. About the team You will join a team of great team of engineers and applied scientists with a proven track record of solving highly complex, ambiguous problems — work that has produced patents and publications at top-tier conferences. The team has direct visibility to senior Prime Video leadership, and collaborates broadly across Commerce, Content, and Platform teams to shape how customers discover, subscribe to, and engage with video content. This is a team that operates at the intersection of rigorous research and real-world impact, where your ideas move from whiteboard to production for hundreds of millions of customers.
US, CA, Palo Alto
Amazon Advertising is one of Amazon's fastest growing and most profitable businesses. Amazon's advertising portfolio helps merchants, retail vendors, and brand owners succeed via native advertising, which grows incremental sales of their products sold through Amazon. The primary goals are to help shoppers discover new products they love, be the most efficient way for advertisers to meet their business objectives, and build a sustainable business that continuously innovates on behalf of customers. Our products and solutions are strategically important to enable our Retail and Marketplace businesses to drive long-term growth. We deliver billions of ad impressions and millions of clicks and break fresh ground in product and technical innovations every day! Amazon continues to develop its advertising program. Ads run in our Stores (including Consumer Stores, Books, Amazon Business, Whole Foods Market, and Fresh) and Media and Entertainment publishers (including Fire TV, Fire Tablets, Kindle, Alexa, Twitch, Prime Video, Freevee, Amazon Music, MiniTV, Audible, IMDb, and others). In addition to these first-party (1P) publishers, we also deliver ads on third-party (3P) publishers. We have a number of ad products, including Sponsored Products and Sponsored Brands, display and video products for smaller brands, including Sponsored Display and Sponsored TV. We also operate ad tech products, including Amazon Marketing Cloud (a clean-room for advertisers), Amazon Publisher Cloud (a clean-room for publishers), and Amazon DSP (an enterprise-level buying tool that brings together our ad tech for buying video, audio, and display ads). Key job responsibilities This role is focused on diving deep into Amazon Ads data, especially full funnel ads campaigns, a new AI-driven workflow provided to advertisers. Rolling out this workflow at scale is critical for Amazon in 2026.
IL, Tel Aviv
Are you a scientist interested in pushing the state of the art in machine learning and recommendation systems? Are you interested in working on novel ideas that can positively impact millions of customers? Do you wish you had access to large datasets and tremendous computational resources? Answer yes to any of these questions and you will be a great fit for our team at Amazon. Our team is part of Amazon’s Personalization organization, a high-performing group that leverages Amazon’s expertise in machine learning, big data, distributed systems, and user experience design to deliver the best shopping experiences for our customers. Our team builds large-scale machine-learning solutions that delight customers with personzlized content recommendations, at the right time, with the right level of explanation. As an Applied Scientist in our team, you will be responsible for the research, design, and development of new AI technologies for personalization. You will adopt or invent new machine learning and analytical techniques in the realm of recommendations and large language models. You will collaborate with scientists, engineers, and product partners locally and abroad. Your work will include inventing, experimenting with, and launching new features, products and systems. Please visit https://www.amazon.science for more information.
IL, Tel Aviv
Are you a scientist interested in pushing the state of the art in machine learning and recommendation systems? Are you interested in working on novel ideas that can positively impact millions of customers? Do you wish you had access to large datasets and tremendous computational resources? Answer yes to any of these questions and you will be a great fit for our team at Amazon. Our team is part of Amazon’s Personalization organization, a high-performing group that leverages Amazon’s expertise in machine learning, big data, distributed systems, and user experience design to deliver the best shopping experiences for our customers. Our team builds large-scale machine-learning solutions that delight customers with personzlized content recommendations, at the right time, with the right level of explanation. As an Applied Scientist in our team, you will be responsible for the research, design, and development of new AI technologies for personalization. You will adopt or invent new machine learning and analytical techniques in the realm of recommendations and large language models. You will collaborate with scientists, engineers, and product partners locally and abroad. Your work will include inventing, experimenting with, and launching new features, products and systems. Please visit https://www.amazon.science for more information.
US, WA, Bellevue
Are you passionate about applying machine learning, time series forecasting, and operations research to transform the delivery of heavy and bulky items for Amazon customers? Are you excited about working with large-scale operational data and developing models that drive real business impact? If so, the Amazon Extra Large (AMXL) Science team may be the right fit for you. AMXL is Amazon's specialized business for delivering heavy and bulky items — appliances, furniture, fitness equipment, and mattresses — with a premium customer experience that includes room-of-choice delivery, at-home installations, and assembly services. In this role, you will leverage large-scale operational data to develop and deploy predictive models and optimization solutions that solve real-world logistics and fulfillment challenges, partnering closely with scientists, engineers, and business stakeholders. Key job responsibilities Apply machine learning, statistical modeling, time series analysis, and operations research techniques to build solutions for delivery routing, capacity planning, demand forecasting, workforce scheduling, and network optimization Analyze large-scale historical and real-time operational data to surface efficiency patterns, bottlenecks, and emerging trends across the AMXL network Develop, validate, and deploy models that improve cost-to-serve and customer experience Partner with cross-functional teams to implement data-driven strategies and measure impact Build scalable, automated pipelines for data ingestion, feature engineering, model training, and validation Monitor deployed model performance and communicate results through clear reporting on key operational and business metrics A day in the life You'll be part of a small, collaborative team of scientists who move fast and care deeply about the problems they solve. A typical week might involve whiteboarding a new forecasting approach with a senior scientist, partnering with engineers to push a model into production, deep-diving into operational data to understand why a metric moved, or presenting your findings to business leaders who will act on them. The work is high-visibility and high-impact. The models you build will directly influence how millions of heavy and bulky items reach customers. About the team The AMXL Science team is a worldwide group of data scientists, applied scientists, and product managers solving Amazon's most complex heavy bulky supply chain challenges. We build forecasting models, capacity planning systems, and optimization tools that directly impact millions of customer deliveries. Our culture values scientific rigor, measurable business impact, and clear communication. We start with baselines, earn complexity, and partner closely with operations to ensure our work drives real decisions. You'll tackle problems where logistics constraints demand creative, data-driven solutions — and see your models shape labor planning, routing, and customer experience at scale.
US, WA, Seattle
This role will develop Economic and Econometric models and thought leadership on projects that span our business, with a particular focus on supply chain and inventory selection. Through the lens of economics, you will develop a deeper understanding of how customers value our selection and interact with Amazon's store to make shopping easier. You will be a key and senior scientist, advising Amazon leaders how to evaluate selection and understand customers. You will work on developing frameworks and scaleable, repeatable models supporting optimal pricing and policy in the two-sided marketplace that is central to Amazon's business. The pricing for Amazon services is complex. You will partner with science and technology teams across Amazon including Supply Chain, Operations, Retail, FBA, Consumer Pricing, and Finance. Key job responsibilities The ideal candidate will have extensive Economics knowledge, demonstrated strength in practical and policy relevant structural econometrics, strong collaboration skills, proven ability to lead highly ambiguous and large projects, and a drive to deliver results. Ability to incorporate AI tools and methods into your work is highly valued. They will work closely with Economists, Data/Applied Scientists, Software Engineers and Product Managers to integrate economic insights into policy and systems production. About the team The Stores Economics and Sciences team is a central science team that supports Amazon's Retail and Supply Chain leadership. We tackle some of Amazon's most challenging economics and machine learning problems, where our mandate is to impact the business on massive scale.
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Amazon Research Awards

Collaborating with scientists around the world to fund research, share knowledge and encourage innovation.