AWS Cryptography call for proposals - Fall 2024

Setting the standard for cryptography at Amazon.

About this CFP

Amazon’s mission is to provide customers with the world’s most secure computing environment. We are the stewards of cryptography within Amazon, and we set the standard for the use and implementation of such technologies across the organization. Cryptography builds and maintains customer trust by protecting users’ applications and data in use, in transit, and at rest.

We seek proposals in these areas:

Primitives and protocols

  • Formal proof of security properties for cryptographic primitives
  • Practical optimizations for cryptographic transport protocols
  • Cryptanalysis of standard algorithms and protocols
  • Wide-block ciphers and new efficient symmetric encryption modes based on existing primitives
  • MPC-friendly symmetric primitives
  • Novel cryptographic constructions using quantum resistant primitives, including threshold signatures and oblivious pseudo-random functions

Open source and verification

  • Formal, static verification of open source cryptographic software, including verification of freedom from side-channel attacks
  • Verified optimization of cryptographic code, particularly for 64-bit x86, Armv8.x, and Armv9.x ISAs and their associated micro-architectures
  • Verification of randomized algorithms

Theory and novel applications

  • Fundamental research of the feasibility of a cryptographically-relevant quantum computer
  • Addressing adversarial behavior in the AI space, including watermarking and provenance mechanisms for AI-generated content
  • Improved practical FHE bootstrapping algorithms for cloud environments
  • Compilers and development tools for FHE and MPC
  • A production-quality math library for FHE
  • Architectures and protocols for cloud-based collaboration of multiple organizations

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 $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 theory or application? Please provide information about your specific domain.
  2. What are the current applications of your work?
  3. What are potential applications of your work to Amazon?
  4. What assumptions are made by your work? What are issues that may invalidate the trustworthiness of results?
  5. If your work involves the development and maintenance of a tool:
    1. Under what license is your tool released?
    2. What training and tutorial material is available?
    3. Is your tool actively maintained (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 Amazon and the development of the scientific community in cryptography. Amazon's commitment to developing the scientific community includes increasing the number of students working on cryptography and at the undergraduate and graduate levels. We are also committed to increasing the diversity of the cryptography community at all levels. We particularly welcome proposals that further these goals.

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.-

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

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MULTIPLE POSITIONS AVAILABLE Employer: AMAZON.COM SERVICES LLC Offered Position: Applied Scientist III Job Location: Seattle, Washington Job Number: AMZ10037670 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
US, NY, New York
About Sponsored Products and Brands: The Sponsored Products and Brands (SPB) organization at Amazon Ads is re-imagining the advertising landscape through industry leading generative AI technologies, revolutionizing how millions of customers discover products and engage with brands across Amazon.com and beyond. We are at the forefront of re-inventing advertising experiences, bridging human creativity with artificial intelligence to transform every aspect of the advertising lifecycle from ad creation and optimization to performance analysis and customer insights. We are a passionate group of innovators dedicated to developing responsible and intelligent AI technologies that balance the needs of advertisers, enhance the shopping experience, and strengthen the marketplace. If you're energized by solving complex challenges and pushing the boundaries of what's possible with AI, join us in shaping the future of advertising. About Our Team: The Brand Beacon team is responsible for inventing impressions offerings for brands to increase share of voice via premium experiences, helping brands get discovered, acquire new customers and sustainably grow customer lifetime value. We build end-to-end solutions that enable brands to drive discovery, visibility and share of voice. This includes building advertiser controls, shopper experiences, monetization strategies and optimization features. We succeed when (1) shoppers discover, engage and build affinity with brands and (2) brands can grow their business at scale with our advertising products. About This Role: As an Applied Scientist on our team, you will: * Develop AI solutions for advertiser and shopper experiences. Build monetization and optimization systems that leverage generative models to value and improve campaign performance. * Define a long-term science vision and roadmap for our Brand Beacon advertising business, driven from our customers' needs, translating that direction into specific plans for applied scientists and engineering teams. This role combines science leadership, organizational ability, technical strength, product focus, and business understanding. * Design and conduct A/B experiments to evaluate proposed solutions based on in-depth data analyses. * Effectively communicate technical and non-technical ideas with teammates and stakeholders; * Stay up-to-date with advancements and the latest modeling techniques in the field. * Think big about the arc of development of Gen AI over a multi-year horizon and identify new opportunities to apply these technologies to solve real-world problems. #GenAI
US, WA, Seattle
Amazon Web Services (AWS) provides a highly reliable, scalable, low-cost infrastructure platform in the cloud that powers hundreds of thousands of businesses in 190 countries around the world. We are hiring an Applied Scientist in our AWS Sales Science & Economics team. The team uses machine learning, econometrics, and data science to optimize AWS’s service catalogue, driving customer engagement and generating insights to guide AWS sales strategy. We use detailed customer behavioral and usage data to predict and understand what customers want from AWS. Key job responsibilities As an Applied Scientist, you will apply the latest research, state of the art machine learning and GenAI to build highly scalable models in support of predictive research and products used across AWS Sales and leadership. You will be responsible for designing and executing science experiments in short and agile cycles. You will use the latest AWS technologies in Machine Learning, Data Science, and AI. You will work closely with business leaders to identify opportunities to drive business growth by applying machine learning and building out predictive models to support analytics and insights. The ideal candidate will be curious and able to learn new technologies quickly. You will have hands-on experience building data science and machine learning pipelines in production working with large scale data sets. You are passionate about sharing your knowledge to enable others. You empathize with the needs of our customers and align your work accordingly, and provide thought leadership and guidance across the organization. A day in the life You will start your day reviewing experimental results and refining model architectures based on new insights. You might spend the morning prototyping a novel approach to a customer-facing problem, then shift to a design review with engineering partners in the afternoon to align on how your solution integrates into production systems. Along the way, you will mentor junior scientists, contribute to peer reviews, and stay connected to the latest research through reading groups and internal science discussions. Your contributions will move from research notebooks to live systems that customers interact with every day. About the team Our team is focused on applying advanced science and machine learning to build intelligent systems that improve the Amazon experience. We value collaboration, intellectual rigor, and a willingness to explore new ideas. You will work alongside scientists and engineers who are committed to turning ambitious research into practical, high-impact solutions. We are investing in the next generation of machine learning capabilities and are looking for team members who are excited to help define that future.
US, CA, San Francisco
The Central Science Team within Amazon’s People Experience and Technology org (PXTCS) uses economics, behavioral science, statistics, and machine learning to proactively identify mechanisms and process improvements which simultaneously improve Amazon and the lives, well-being, and the value of work to Amazonians. We are an interdisciplinary team, which combines the talents of science and engineering to develop and deliver solutions that measurably achieve this goal. We are looking for an Applied Scientist to build production machine learning solutions that improve employee experiences and inform workforce decisions. You will work on problems spanning predictive modeling, natural language processing, recommendation systems, personalization, generative AI, and causal evaluation. These solutions will predict workforce outcomes, identify individual and organizational needs, recommend targeted actions, and measure the causal impact of programs, products, and policies across diverse employee populations and business contexts. As an Applied Scientist, you will develop models and algorithms from prototype through production. You will collaborate with other scientists and economists to combine machine learning with causal inference and experimentation, allowing teams to understand both what is likely to happen and which actions will improve outcomes. You will also work with product managers, engineers, and business partners to translate business needs into technical solutions and communicate methods and results to technical and nontechnical audiences. Key job responsibilities • Design, develop, and deploy machine learning solutions in production environments. • Develop solutions using techniques that include predictive modeling, deep learning, natural language processing, recommendation systems, personalization, and generative AI. • Build models that predict workforce outcomes, identify employee and organizational needs, and recommend targeted actions. • Partner with economists and other scientists to design causal evaluations and experimental frameworks that measure the impact of programs, products, and policies. • Combine predictive models with causal estimates to help business partners identify effective actions and make evidence-based decisions. • Collaborate with product managers, engineers, and business partners to translate business requirements into modeling approaches and contribute to technical design and roadmap decisions. • Evaluate model accuracy, performance, calibration, and limitations, and identify opportunities for improvement. • Communicate technical concepts, methods, results, and recommendations to technical peers and business partners. A day in the life • Analyze data to investigate model performance or understand an unexpected result from a causal evaluation. • Brainstorm modeling and evaluation approaches with applied scientists and economists on the team. • Develop and test model features, recommendation methods, or generative AI applications. • Design or analyze experiments and observational studies to estimate the causal impact of programs, products, or policies. • Run simulations, offline evaluations, or backtests to assess model performance. • Meet with product, engineering, and business partners to review requirements, data, designs, and implementation decisions. • Review code changes or technical design documents from scientists and engineers. • Write and present documents covering methods, results, limitations, and recommendations. About the team The People eXperience and Technology Central Science Team (PXTCS) 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. We are an interdisciplinary team that combines the talents of science and engineering to develop and deliver solutions that measurably achieve this goal.
US, WA, Seattle
Are you excited to play a strategic role in defining the customer experience on Tablets? Come join a dynamic, customer-obsessed, world-class science team to completely reshape the customer experience on our tablets. Key job responsibilities Using Amazon’s large-scale computing resources, you will design and deploy state-of-the-art recommendation models. You will ask research questions about customer behavior, design state-of-the-art models that help customers discover content, and deploy these models to production alongside other engineers. You will participate in the Amazon ML community and mentor other engineers with a strong interest in and knowledge of ML and generative AI. Your work will directly benefit customers! A day in the life We are looking for a passionate, hard-working, and talented Applied Scientist who has experience developing state-of-the-art models and deploying them to production. You will have an opportunity to make an enormous impact on the design, architecture, and implementation of products used everyday by real customers! About the team The Alexa Tablet team is a world-class team that delivers high-quality, innovative products that are loved by our customers. Our team focuses on spinning many of Amazon’s flywheels with bar-raising mobile experiences on our tablets. Over the last 12 years, we have built 4.0+ star rated products, and we continue to look for ways to scale our business. Join us as we continue our ambitious journey which will give you the opportunity to deliver disruptive products with global impact.
IN, KA, Bengaluru
Amazon.com’s Product Detail Page team is looking for talented, motivated and passionate applied scientist to be part of the design and development of a highly scalable multi-tiered shopping application to provide the best possible online shopping experience for Amazon customers world-wide. Our team is comprised of talented applied scientists, developers, testers, program managers, designers and product managers tasked with the singular goal to create THE world's best buying experience. Scientists on this team develop the next-generation technologies and experiences that change how millions interact and shop online. To provide the best possible online shopping at the scale of the web requires ideas from every area of computer science, including distributed computing, large-scale system design, machine learning, natural language processing, data compression and user interface design; the list goes on and is growing every day. We need our scientists to be versatile and always eager to tackle new problems as we continue to push technology forward. Our team leverages sophisticated econometric, machine learning, and big data technologies to help customers to discover the right products at the right prices from millions of trusted sellers billions of times a day. If you are looking for a career-defining opportunity on one of the most customer centric and business impacting teams within Amazon, we’d love to hear from you. We are looking for an Applied Scientist to help build the next generation of Detail Page optimization algorithms. These new set of algorithms will incorporate the continually changing preferences of our customers and continue to scale with numerous new programs that Amazon is introducing for our customers. You will work with multiple Amazon businesses and programs to identify big business opportunities and propose new business features and technical systems to improve customer experience on Amazon Detail Page, Search Page and many other widgets throughout the website. You will be responsible for the quality of algorithm design and will get the opportunity to present your ideas and share results of your deliverables with Amazon executives on a frequent basis. You will get an opportunity to work with senior scientists to define and enforce broad, company-wide technical standards in optimization techniques, statistical modeling and simulation techniques, and/or data analytics.
US, WA, Seattle
Applied Scientist II (AMZ1513176) (Multiple Positions), Amazon Data Services, Inc., Seattle, WA. 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. Research and implement novel ML and statistical approaches to add value to the business. Mentor junior engineers and scientists. (AMZ1513176) 40 hrs/week, Mon-Fri, 8:00 a.m. - 5:00 p.m. Salary Range: $163,617 - $193,200/yr. Amazon.com is an Equal Opportunity – Affirmative Action Employer – Minority/Female/Disability/Veteran/Gender Identity/Sexual Orientation MINIMUM REQUIREMENTS: Master's degree or foreign equivalent in Computer Science, Machine Learning, Statistics, or a related field and (1) one year 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 in Computer Science, Machine Learning, Statistics, or a related field and (5) five years of research or work experience in a related occupation as equivalent to the Master's degree and one year of research or work experience. Must have (1) one year of research or work experience in the following skill(s): programming in Java, C++, Python, or equivalent programming language; and conducting the analysis and development of various supervised and unsupervised machine learning models for moderately complex projects in business, science, or engineering. Employer will accept any suitable combination of education, training or experience. Multiple Positions Available. Amazon is a total compensation company. Depending 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
US, CA, Pasadena
We are seeking Research Scientists to join our team. In this role, you will develop and deploy the science of safe autonomy on highly dynamic robots, advancing the frontier through both foundational research and realization on hardware. You will contribute to achieving safe autonomy across three key areas: control barrier function (CBF) theory for robust and performant safety on hardware; safe reinforcement learning for agile whole-body control; and layered safety filters that interface with learning, perception, and semantic reasoning systems. You will validate your work experimentally on state-of-the-art robotic platforms — removing bottlenecks to deployment and enabling robots to safely operate around humans. You will work with the inventor of CBFs, as well as top scientists and engineers at Amazon developing the next generation of safe autonomy. Key job responsibilities - Advance the science of safe autonomy from formal foundations to the integration with learning and perception to validation on hardware — with particular emphasis on methods that bridge these domains. - Test and validate hardware, with a focus on next generation robotic systems. Including locomotion, manipulation and loco-manipulation. - Leverage the deployments on hardware to validate the underlying science, identifying gaps between theory and practice that drive the next cycle of research. hardware to validate the underlying science, identifying gaps between theory and practice that drive the next cycle of research. - Publish research at top-tier robotics, control, and ML venues, and contribute to Amazon’s scientific reputation in advanced robotics. - Collaborate with Lab and Amazon production teams to move research into robots deployed at Amazon scale. 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! About the team The Safe Autonomy Frontiers (SAF) Lab is the first industry research lab dedicated to safe autonomy, founded by the inventor of control barrier functions. We are developing a universal safety layer for the next generation of robotic systems: mobile robots, manipulators, quadrupeds, and humanoids. Here you will advance performant safety for highly dynamic robots — CBF theory integrated with perception and learning, evaluated on next-generation platforms — and your work will underpin robots operating alongside people at Amazon’s unprecedented scale.
US, WA, Seattle
nnovators 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 extreme. We focus on creating entirely new products and services with a goal of positively impacting the lives of our customers. No industries or subject areas are out of bounds. If you’re interested in innovating at scale to address big challenges in the world, this is the team for you. Here at Amazon, we embrace our differences. We are committed to furthering our culture of inclusion. We have thirteen employee-led affinity groups, reaching 40,000 employees in over 190 chapters globally. We are constantly learning through programs that are local, regional, and global. Amazon’s culture of inclusion is reinforced within our 16 Leadership Principles, which remind team members to seek diverse perspectives, learn and be curious, and earn trust. Our team highly values work-life balance, mentorship and career growth. We believe striking the right balance between your personal and professional life is critical to life-long happiness and fulfillment. We care about your career growth and strive to assign projects and offer training that will challenge you to become your best.
US, WA, Bellevue
Are you curious about turning complex data into actionable insights that shape how millions of customers experience Amazon? Do you enjoy building analytical models, testing hypotheses, and seeing your work drive real business decisions? We are looking for a Data Scientist to join our team at Amazon. In this role, you will apply statistical techniques, machine learning, and data analysis to solve well-defined business problems and deliver measurable improvements. You will work with large-scale datasets from multiple sources, build and validate models, and create metrics that quantify impact. This is an opportunity for a self-starter who is comfortable with ambiguity in data, thrives on collaboration with science and engineering partners, and is eager to grow their craft in a fast-paced environment. Key job responsibilities - Use statistical methods, machine learning algorithms, and data analysis techniques to translate well-defined business problems into data science solutions that improve processes and systems. - Gather, clean, and integrate large datasets from multiple sources to build and validate models, ensuring data integrity and adherence to best practices throughout the pipeline. - Design and deliver metrics, visualizations, and reports that compare results against benchmarks and original project goals, enabling clear and informed decision-making for stakeholders. - Collaborate with business, science, and engineering teams to understand customer needs, identify opportunities, and develop scalable analytical solutions using tools such as Python, R, or SQL. - Evaluate opportunities to integrate generative artificial intelligence tools into workflows, refining outputs and applying responsible practices to augment productivity and solution quality. About the team Our team is focused on using data science to help Amazon make smarter, faster decisions that benefit customers. We build analytical models and machine learning solutions that operate at scale, and we value rigorous methodology paired with clear communication. You will join a collaborative group of scientists and engineers who are passionate about learning from one another and pushing the boundaries of what data can do. If you are excited about growing your career in an inclusive, supportive environment where your contributions have tangible impact, we would love to hear from you.
CH, Zurich
Are you a MS or PhD student interested in a 2026 Applied Science Internship in the field of Robotics? Do you enjoy diving deep into hard technical problems and coming up with solutions that enable successful products that improve the lives of people in a meaningful way? If this describes you, come join our research teams at Amazon. Key job responsibilities As an Applied Science Intern, you will have access to large datasets with billions of images and video to build large-scale machine learning systems. Additionally, you will analyze and model terabytes of text, images, and other types of data to solve real-world problems and translate business and functional requirements into quick prototypes or proofs of concept. We are looking for scientists capable of using a variety of domain expertise combined with machine learning and statistical techniques to invent, design, evangelize, and implement state-of-the-art solutions for never-before-solved problems.
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Amazon Research Awards

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