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Automated Reasoning Call for Proposals — Fall 2023

Systems assurance by mathematical proof

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About this CFP

Amazon is committed to helping customers achieve the highest levels of security, availability, and robustness in the cloud. Automated reasoning is the application of mathematical logic to answer questions and prove properties about critical computer systems. Using automated reasoning, Amazon is able to detect previously missed misconfigurations, or show their absence, and to prove that protocols and programs work as intended. Our work in provable security and privacy aims to provides higher assurance for customers. We anticipate funding research in these categories:

  • Automated reasoning
  • Abstract interpretation
  • Correct-by-construction software
  • Dafny
  • Efficient reasoning with quantifiers
  • Improvements to SAT, SMT, and CHC solvers
  • Model checking
  • Novel applications of automated reasoning
  • Provable Privacy
  • Software synthesis and optimization
  • Software verification, e.g., C, Rust, Java
  • Static analysis
  • Theorem proving
  • The use of automated reasoning to improve generative AI techniques
  • Using automated reasoning in combination with generative AI techniques
  • Verification of distributed protocols and systems
  • Verification of randomized algorithms

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 $80,000 USD on average
  • AWS Promotional Credits, no more than $20,000 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 should be prepared according to the proposal template. Proposals should answer the following questions:

  1. Does your work target analysis of protocols, code, or configuration? Please provide information about your domain and the type of analysis.
  2. What are the current applications of your work? (e.g., libraries, codebases, or industry code).
  3. What are potential applications of your work to Amazon?
  4. What assumptions are made by your work? If the techniques proposed are sound: What are issues that may invalidate this result?
  5. If your work involves the development and maintenance of a tool:
    1. Under what license is or will your tool be released?
    2. What on-boarding/tutorial material is available?
    3. Is your tool actively maintained (i.e., commits within last 3 months)? How many active contributors does your project have?

Selection criteria

ARA funding decisions will be based on potential impact to automated reasoning research, and the development of the automated reasoning scientific community. Amazon's commitment to developing the automated reasoning scientific community includes increasing the number of university researchers engaged in automated reasoning research. We are also committed to increasing the diversity of the automated reasoning community at all levels.

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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Senior Applied Scientist, Special Projects
US, WA, Seattle
Innovators wanted! Are you an entrepreneur? A builder? A dreamer? This role is part of an Amazon Special Projects team that takes the company’s Think Big leadership principle to the limits. If you’re interested in innovating at scale to address big challenges in the world, this is the team for you. As a Senior Applied Scientist on our team, you will focus on building state-of-the-art ML models for healthcare. Our team rewards curiosity while maintaining a laser-focus in bringing products to market. Competitive candidates are responsive, flexible, and able to succeed within an open, collaborative, entrepreneurial, startup-like environment. At the forefront of both academic and applied research in this product area, you have the opportunity to work together with a diverse and talented team of scientists, engineers, and product managers and collaborate with other teams. This role offers a unique opportunity to work on projects that could fundamentally transform healthcare outcomes. Key job responsibilities In this role, you will: • Design and implement novel AI/ML solutions for complex healthcare challenges • Drive advancements in machine learning and data science • Balance theoretical knowledge with practical implementation • Work closely with customers and partners to understand their requirements • Navigate ambiguity and create clarity in early-stage product development • Collaborate with cross-functional teams while fostering innovation in a collaborative work environment to deliver impactful solutions • Establish best practices for ML experimentation, evaluation, development and deployment • Partner with leadership to define roadmap and strategic initiatives You’ll need a strong background in AI/ML, proven leadership skills, and the ability to translate complex concepts into actionable plans. You’ll also need to effectively translate research findings into practical solutions. A day in the life You will solve real-world problems by getting and analyzing large amounts of data, generate insights and opportunities, design simulations and experiments, and develop statistical and ML models. The team is driven by business needs, which requires collaboration with other Scientists, Engineers, and Product Managers across the Special Projects organization. You will prepare written and verbal presentations to share insights to audiences of varying levels of technical sophistication. About the team We represent Amazon's ambitious vision to solve the world's most pressing challenges. We are exploring new approaches to enhance research practices in the healthcare space, leveraging Amazon's scale and technological expertise. We operate with the agility of a startup while backed by Amazon's resources and operational excellence. We're looking for builders who are excited about working on ambitious, undefined problems and are comfortable with ambiguity.
Applied Scientist II, IESP Digital Payments
BR, SP, Sao Paulo
Do you like working on projects that are highly visible and are tied closely to Amazon’s growth? Are you seeking an environment where you can drive innovation leveraging the scalability and innovation with Amazon's AWS cloud services? The Amazon IESP Digital Payments & Emerging Team is hiring Applied Scientists to work in our Machine Learning team in São Paulo, Brazil. The Payments team designs and builds scalable payment systems that power Amazon's checkout and financial services across emerging countries (Brazil, Mexico, Australia, Singapore, and more). We tackle complex challenges in payment orchestration, fraud detection, and regional payment method integration to drive conversion and deliver seamless experiences at scale. Key job responsibilities About you You want to make changes that help millions of customers. You don’t want to make something 10% better as a part of an enormous team. Rather, you want to innovate with a small community of passionate peers. You have experience in analytics, machine learning, LLMs and Agentic AI, and a desire to learn more about these subjects. You want a trusted role in strategy and product design. You put the customer first in your thinking. You have great problem solving skills. You research the latest data technologies and use them to help you innovate and keep costs low. You have great judgment and communication skills, and a history of delivering results. Your Responsibilities - Define and own complex machine learning solutions in the consumer space, including targeting, measurement, creative optimization, and multivariate testing. - Design, implement, and evolve Agentic AI systems that can autonomously perceive their environment, reason about context, and take actions across business workflows—while ensuring human-in-the-loop oversight for high-stakes decisions. - Influence the broader team's approach to integrating machine learning into business workflows. - Advise leadership, both tech and non-tech. - Support technical trade-offs between short-term needs and long-term goals.
Economist I, Capacity Economics, AWS Central Economics & Science
US, WA, Seattle
The AWS Central Economics & Science team is looking for a PhD economist. The ideal candidate will be proficient in both reduced form and structural estimation and, most importantly, will be eager to learn new methods where applicable. The ideal candidate should be a problem-solver first, with an ability to bring theoretical frameworks to real-world business problems, working backwards from the business problem rather than from any particular solution method. In this role, you will become a subject-matter expert in cloud infrastructure, creating theoretical frameworks, data-driven insights, and statistical models to help AWS serve its total demand at a lower cost. You will work closely with finance, product, and engineering teams—as well as economists and other scientists—to understand complex systems and products, and will have the freedom to propose, explore, and deliver on a wide variety of projects that emerge from your research. Our team functions like a start-up within the AWS ecosystem—we have the freedom to identify greenfield problems that other economists have not explored yet, and build trust with the business through delivering valuable insights and policy changes. Most importantly, we solve problems at a massive scale and do it in a collaborative, curious, supportive, and fun environment. Key job responsibilities - Become a subject-matter expert in various areas of infrastructure, cost management, and transfer pricing. - Deliver insights that leads to policy changes through analysis, modeling, and theoretical frameworks. - Collaborate closely with non-economist business partners to communicate insights, implement solutions through production models, and develop a research agenda. About the team ACES works on high-impact projects for AWS service teams and leadership. This position will support the cost and transfer pricing optimization team to help AWS continue to scale its infrastructure efficiently in a fast-changing technological and competitive environment.
Senior Data Scientist, Amazon Leo
US, WA, Bellevue
Amazon Leo is Amazon’s low Earth orbit satellite broadband network. Its mission is to deliver fast, reliable internet to customers and communities around the world, and we’ve designed the system with the capacity, flexibility, and performance to serve a wide range of customers, from individual households to schools, hospitals, businesses, government agencies, and other organizations operating in locations without reliable connectivity. Export Control Requirement: Due to applicable export control laws and regulations, candidates must be a U.S. citizen or national, U.S. permanent resident (i.e., current Green Card holder), or lawfully admitted into the U.S. as a refugee or granted asylum. As a Senior Data Scientist (DS), you will drive the development and implementation of advanced analytics and machine learning solutions. You will work on critical initiatives including natural language processing for non-conformance analysis, statistical process controls (SPC) for test optimization, and equipment predictive maintenance models to enable manufacturing rate acceleration. Your work will directly influence Kuiper’s production manufacturing workflow. You are an analytical problem solver who enjoys diving into data from various businesses, is excited about investigations and algorithms, can multi-task, and can credibly interface between scientists, engineers, and business stakeholders. Your expertise in synthesizing and communicating insights and recommendations to audiences of varying levels of technical sophistication will enable you to answer specific business questions and innovate for the future. Key job responsibilities Lead the design and implementation of ML/LLM solutions to analyze manufacturing data and identify failure patterns and operational risks Design predictive models for statistical process control and equipment maintenance optimization Build production-ready ML pipelines leveraging AWS services (e.g., SageMaker, Bedrock, AWS Glue) Formalize assumptions about how models are expected to behave, creating definitions of outliers, developing methods to systematically identify these outliers, and explaining why they are reasonable or identifying fixes for them Develop and test model enhancements, running computational experiments, and fine-tuning model parameters for new models Collaborate with engineering teams to translate complex manufacturing challenges into data-driven solutions Drive consensus on metrics and analysis approaches to support business strategy Write documents and create compelling visualizations and presentations to communicate insights to stakeholders Mentor team members and drive data science best practices across the organization About the team Established in 2023 as ProdOps was preparing to transition from development into full-rate production, OCC was purpose-built to ensure that as manufacturing scaled, the most critical problems would be identified, solved, and prevented from recurring through a single integrated operating system. OCC focuses on the most critical problems for ProdOps at each phase of production. The team operates as a closed-loop flywheel where each rotation identifies value, solves problems, implements change, and generates new data that feeds the next cycle. Every rotation compounds returns.
Applied Scientist, Fauna
US, NY, New York
We are seeking an Applied Scientist to lead the development of evaluation frameworks and data collection protocols for robotic capabilities. In this role, you will focus on designing how we measure, stress-test, and improve robot behavior across a wide range of real-world tasks. Your work will play a critical role in shaping how policies are validated and how high-quality datasets are generated to accelerate system performance. You will operate at the intersection of robotics, machine learning, and human-in-the-loop systems, building the infrastructure and methodologies that connect teleoperation, evaluation, and learning. This includes developing evaluation policies, defining task structures, and contributing to operator-facing interfaces that enable scalable and reliable data collection. The ideal candidate is highly experimental, systems-oriented, and comfortable working across software, robotics, and data pipelines, with a strong focus on turning ambiguous capability goals into measurable and actionable evaluation systems. Key job responsibilities - Design and implement evaluation frameworks to measure robot capabilities across structured tasks, edge cases, and real-world scenarios - Develop task definitions, success criteria, and benchmarking methodologies that enable consistent and reproducible evaluation of policies - Create and refine data collection protocols that generate high-quality, task-relevant datasets aligned with model development needs - Build and iterate on teleoperation workflows and operator interfaces to support efficient, reliable, and scalable data collection - Analyze evaluation results and collected data to identify performance gaps, failure modes, and opportunities for targeted data collection - Collaborate with engineering teams to integrate evaluation tooling, logging systems, and data pipelines into the broader robotics stack - Stay current with advances in robotics, evaluation methodologies, and human-in-the-loop learning to continuously improve internal approaches - Lead technical projects from conception through production deployment - Mentor junior scientists and engineers
Sr. Applied Scientist, Prime Video - Generative AI (Video)
US, CA, Sunnyvale
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 subscriptions such as Apple TV+, HBO Max, Peacock, 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? Prime Video's technology teams are creating best-in-class digital video experience. As a Prime Video team member, you’ll have end-to-end ownership of the product, user experience, design, and technology required to deliver state-of-the-art experiences for our customers. You’ll get to work on projects that are fast-paced, challenging, and varied. You’ll also be able to experiment with new possibilities, take risks, and collaborate with remarkable people. We’ll look for you to bring your diverse perspectives, ideas, and skill-sets to make Prime Video even better for our customers. With global opportunities for talented technologists, you can decide where a career Prime Video Tech takes you! Key job responsibilities • Build generative AI models that create production-ready content, including movie content, localized assets, and visual marketing materials used across Prime Video's global platform. • Drive end-to-end machine learning projects that have a high degree of ambiguity, scale, complexity. • Build machine learning models, perform proof-of-concept, experiment, optimize, and deploy your models. • Run experiments, gather data, and perform statistical analysis. • Establish scalable, efficient, automated processes for large-scale data analysis, machine-learning model development, model validation and serving. • Research new and innovative machine learning approaches. • Share knowledge and research outcomes via internal and external conferences and journal publications About the team Prime Video is pioneering the use of Generative AI to empower the next generation of creatives. Our mission is to make world-class media creation accessible, scalable, and efficient. We are seeking an Applied Scientist to advance the state of the art in Generative AI and to deliver these innovations as production-ready systems at Amazon scale. Your work will give creators unprecedented freedom and control while driving new efficiencies across Prime Video’s global content and marketing pipelines. This is a newly formed team within Prime Video Science!
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