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AWS AI call for proposals — Fall 2024

Advancing the frontiers of machine learning.

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About this CFP

AWS offers a broad and deep set of tools for businesses to create impactful machine learning solutions faster. Our mission is to share our learnings and ML capabilities as fully managed services, and put them into the hands of every scientist and developer.

AWS AI aims to advance machine learning research by funding development of open-source tools and research that benefit the machine learning community at large, or impactful research that uses machine learning tools.

We welcome proposals related to machine learning in the areas below:

  1. Generative AI
  2. Governance and responsible AI
  3. Distributed training
  4. Machine learning compilers and compiler based optimizations

Other applied machine learning topics are also welcome.

Timeline

Submission period: September 25, 2024 - November 13, 2024 (11:59PM Pacific Time)

Decision letters will be sent out in March 2025

Award details

Selected Principal Investigators (PIs) may receive the following:

  • Unrestricted funds, no more than $70,000 USD on average
  • AWS Promotional Credits, no more than $50,000 USD on average
  • Training resources, including AWS tutorials and hands-on sessions with Amazon scientists and engineers

Amazon Research Awards (ARA) are structured as one-year unrestricted gifts. The budget should include a list of expected costs specified in USD, and should not include administrative overhead costs. The final award amount will be determined by the awards panel.

Eligibility requirements

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

Proposal requirements

Proposals for this CFP should be prepared according to the proposal template and are encouraged to be a maximum of 5 pages, not including Appendices. In addition, to submit a proposal for this CFP, please also include the following information:

  1. Please list the open-source tools you plan to contribute to.
  2. Please list the AWS ML tools you will use.

Selection criteria

ARA will make the funding decisions based on the potential impact to the research community, quality of the scientific content. We encourage research that uses machine learning tools, for example AWS AI/ML services (Amazon SageMaker, Amazon AI services, Amazon Bedrock).

Expectations from recipients

To the extent deemed reasonable, Award recipients should acknowledge the support from ARA. Award recipients will inform ARA of publications, presentations, code and data releases, blogs/social media posts, and other speaking engagements referencing the results of the supported research or the Award. Award recipients are expected to provide updates and feedback to ARA via surveys or reports on the status of their research. Award recipients will have an opportunity to work with ARA on an informational statement about the awarded project that may be used to generate visibility for their institutions and ARA.

How to apply
When you're ready to submit your proposal, use the button below and follow the instructions on the site.
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Data Scientist, OTS - Data ANCHOR Team
US, TX, Austin
The OTS ANCHOR (Analytics, Insights, and Centralized Hub for OTS Reporting) team is part of the WW IT Operations & RME organization, responsible for delivering data solutions that drive operational excellence across Amazon's global IT infrastructure. We build data pipelines, predictive models, develop analytical intelligence frameworks, and create AI-powered solutions that transform how Amazon manages, triages, and resolves IT operational incidents at scale pointing towards the Letting Data Tell the Story north start vision. We are seeking a Data Scientist to help own the end-to-end data science charter for critical operational workstreams — from forecasting IT service demand and capacity planning to designing intelligent severity triaging models and building the analytical backbone for agentic AI solutions. You will work backwards from complex operational problems to create models and solutions that directly impact the efficiency and reliability of Amazon's IT operations worldwide. Key job responsibilities - Design, develop, and deploy machine learning models for IT operations forecasting, including incident volume prediction, capacity planning, and workforce demand modeling - Build and maintain severity classification and intelligent triaging models that process thousands of daily IT service tickets across global regions - Develop anomaly detection systems to identify emerging patterns in operational data, supporting proactive incident prevention - Apply econometric and statistical methods to measure the impact of operational interventions and inform resource allocation decisions - Partner with engineering teams to productionize ML models via automated pipelines using AWS services (SageMaker, Step Functions, Lambda, Redshift) - Design and conduct experiments to empirically validate model performance and operational impact - Contribute to data quality monitoring frameworks and help maintain standards for operational data integrity - Collaborate with cross-functional teams (ServiceNow platform, Decision Intelligence, Field Operations) to translate analytical insights into actionable recommendations - Communicate findings, model performance, and recommendations to stakeholders and senior leaders through written documents and presentations - Contribute to the team's science roadmap, identifying opportunities to apply ML/AI (including Generative AI) to operational challenges A day in the life Amazon Benefits: 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: 1. Medical, Dental, and Vision Coverage 2. Maternity and Parental Leave Options 3. Paid Time Off (PTO) 4. 401(k) Plan
2027 Applied Science Internship - Robotics - United States
US, MA, North Reading
Robotics Applied Scientist II Intern/Co-op (2027) Are you passionate about robotics and research? Do you want to solve real customer problems through innovative technology? Do you enjoy working on scalable research and projects in a collaborative team environment? Do you want to see your science solutions directly impact millions of customers worldwide? We’re looking for current PhD students with a passion for robotic research and applications to join us in 2027 as Robotics Applied Scientist II Interns/Co-ops to shape the future of robotics and transform automation at Amazon’s scale. By applying to this role, you will be considered for Robotics Applied Scientist II Intern/Co-op (2027) opportunities across various Robotics teams at Amazon with different robotics research focus. Internship positions are available for multiple locations, durations (3 to 6+ months), and year-round start dates (winter, spring, summer, fall). Join us at the forefront of Applied Science, where your contributions will shape the future of Robotics! Key job responsibilities As a Robotics Applied Scientist II Intern/Co-op, you will work alongside global experts to advance the state of the art in robotics and artificial intelligence, tackling innovative problems that bridge the gap between research and real-world robotics implementation to innovate and build solutions on behalf of our customers. We are particularly interested in students with specialization and expertise in one or more of the following research areas: - Robotics - Artificial Intelligence - Robotics Manipulation (e.g., robot arm, grasping, dexterous manipulation, end of arm tools/end effector) - Autonomous Mobile Robots - Mobile Manipulation - Multi-Robot Coordination - Autonomous Navigation - Locomotion - Motion/Path Planning - Controls - Perception - Sensing - Robot Learning - Machine Learning - Computer Vision - Large Language Models (LLM), Vision-Language-Action Models (VLA), Vision-Language-Models (VLM) - World Models - Human-Robot Interaction - Robotics Simulation - Optimization - And related! Key responsibilities may include: - Develop novel, scalable algorithms and/or modeling techniques that advance the state-of-the-art in science areas such as robotics, artificial intelligence, or related - Tackle challenging, innovative research problems within robotics, artificial intelligence, or related that bridge the gap between theoretical advancement and practical robotics implementation - Collaborate with cross-functional teams to solve complex problems, and to communicate research findings clearly, leveraging your expertise in robotics, artificial intelligence, or related - Demonstrate the ability to work independently, thrive in a fast-paced, ever-changing environment - Leverage AI-powered tools where applicable to accelerate research, experimentation, and prototyping. - Critically review and validate outputs from AI tools and automated systems. About the team Explore Robotics Teams at Amazon At Amazon, robotics is where innovative research meets real-world deployment. There are many different specialized robotics teams, including the few highlighted below. Learn more about Robotics at Amazon here: https://www.amazon.science/research-areas/robotics Fulfillment Technologies and Robotics We build dynamic partnerships between people and intelligent machines. This intricate collaboration helps Amazon fulfill orders with unmatched accuracy. Working in symphony with our robotic technology, you’ll have the opportunity to extend your technical capabilities by working alongside some of the industry’s most advanced technologies. This includes our fleet of autonomous mobile robots, sophisticated control software, and technologies like language perception, machine learning, object recognition, and semantic understanding of commands. These technologies help us deliver an ever-improving customer and employee experience, as well as improve the safety of our facilities. Amazon Robotics Amazon Robotics is at the epicenter of robotics innovation. We design, test, and build mobile robots and mechatronic systems. Our offices, labs, test floors, and factories are close together, which means we can design the hardware, write the code, test, build, and watch it all come to life. Our areas of focus include advancements in autonomous mobility, AI, robotic management software, and much more. Fauna Fauna is focused on building capable, safe, and genuinely delightful robots for everyday life. Fauna’s goal is simple: make robots people actually want to live and interact with everyday. Fauna develops tightly integrated hardware and software systems that make it faster, safer, and more intuitive to create real-world robotic products. Fauna’s work spans the full stack: mechanical design, control systems, dynamic modeling, and intelligent software. The focus is not just functionality, but overall experience. Amazon Fulfillment Technologies Amazon Fulfillment Technologies develops tech solutions that create network optimizations for all Amazon sites worldwide. We own network infrastructure and devices in all buildings and labor planning and scheduling technology for fulfillment centers in North America and Europe.
Principal Applied Scientist, FAIM (Full Funnel Agentic Intelligence and Models)
US, NY, New York
The FAIM (Full Funnel Agentic Intelligence and Models) builds the agentic AI systems behind next-generation advertising. The team develops multimodal foundation models and LLM-driven agents that power shopper understanding, audience-aware creative generation, and agentic advertising workflows. As a Principal Applied Scientist for the FAIM team, you will invent the models that help advertisers achieve desired outcomes. Today's state of the art models can setup ad campaigns to a specification, but do not understand advertising strategy well enough to help with abstract goals that real advertisers ask about like "how can I make more money." This is a rare charter to build foundational optimization science where little exists today, spanning campaign recommendation, cross-product budget allocation, incrementality measurement, and long-term-sales modeling. You will set technical direction for a growing team, partner with engineering and product to take models from research to production at Amazon scale, and directly move advertiser ROAS and new-to-brand growth. In this role you will - Own the science vision for developing evaluations of the Ads Agent - Partner with scientists from across Ads to develop best practices for evaluating agent performance both online and offline - Raise the science bar for all agent evaluations developed in Ads. - Own establishing a data driven foundation for making decisions about when new features are ready to launch in Ads Agent. Key job responsibilities - Define the long-term scientific vision for agent evaluations in Ads - Translate ambiguous advertiser needs and competing objectives into a concrete science roadmap. - Invent, prototype, and productionize machine learning and optimization solutions for joint budget allocation across sponsored ad products, spanning the shopper journey from awareness to purchase. - Develop rigorous approaches to incrementality measurement and long-term-sales modeling that ground optimization in true advertiser value. - Design and lead large-scale experiments and analyses to validate hypotheses and guide product direction. - Partner closely with engineering and product to define technical contracts, data schemas, and serving systems that carry models into production. - Raise the technical bar across science and engineering through mentorship, design reviews, and hands-on collaboration. - Grow scientific talent and publish impactful research internally and at top-tier venues.
Research Scientist, SCOT First Inbound
US, NY, New York
The Supply Chain Optimization Technologies (SCOT) organization owns Amazon’s global inventory management systems: we decide what, when, where, and how much we should buy to meet Amazon’s business goals and to make our customers happy. We do this for millions of items, for hundreds of product lines worth billions of dollars of inventory world-wide. Our systems are built entirely in-house, and are automated large-scale business operations, inventory and supply chain planning and optimization systems. We foster new game-changing ideas, creating ever more intelligent and self-learning systems to maximize the efficiency of Amazon's inventory investment and placement decisions. The Inbound Systems team within SCOT seeks a Research Scientist to innovate in SCOT inbound placement decision and capacity management systems. As a research scientist, you will use your experience to initiate the design, development, execution and implementation of scientific research projects. Working closely with fellow scientists, BI engineers and product managers, you will use your experience in modeling, statistics, and simulation to design models of new policies, simulate their performance, and evaluate their benefits and impacts to cost, reliability, and speed of our fulfillment network. Our teams are looking for experience in network and combinatorial optimization, statistical inference, and machine learning. This position requires superior analytical thinking, and ability to apply their technical and statistical knowledge to identify opportunities for real world applications.
Applied Scientist
IN, KA, Bengaluru
Help millions of authors around the world get their books published, discovered, and supported. As one of the first scientists on our new team in Bengaluru, you'll help turn ideas into models authors rely on every day, building agentic solutions with large language models (LLMs), multimodal models, and fine-tuning. Key job responsibilities - Build the multi-agent system behind KDP's author support assistant: orchestration across specialized agents and tools, personalization, and the evaluation that drives its continuous improvement. - Build multimodal models of book attributes, and use them for similar-book search across languages, catalog quality, and category and keyword recommendations. - Post-train open models on KDP expertise (for example with supervised fine-tuning and reinforcement learning), and deploy them where they beat general-purpose models on accuracy, cost, or speed. - Work closely with our scientists in the US and with engineering partners to take your work to production, design rigorous offline and online experiments, and write clear readouts with recommendations. About the team Kindle Direct Publishing (KDP) lets anyone publish a book. We are the science organization for Amazon's Books business, now building our science teams in Bengaluru. Our team works in three connected areas: a support assistant that answers authors' questions from their own account data, in every language KDP supports; multimodal models that use book attributes to keep the catalog trustworthy and help authors reach the right readers; and fine-tuned models that power the assistant and catalog models with KDP expertise. We serve authors, from first-time writers to full-time publishers. You will work closely with engineering, product, and policy partners. We value safety before speed and shared foundations over one-off fixes. Scientists here get dedicated time for innovation, which can lead to patents and conference papers.
Applied Science Manager
IN, KA, Bengaluru
Help authors around the world publish their books, reach readers, and get help when they need it. You'll build and lead our first science team in Bengaluru and shape the assistant authors turn to for answers and the models that keep the Books catalog trustworthy. Key job responsibilities - Hire, develop, and retain a high-performing team of applied scientists across levels, and set its practices for experimentation, evaluation, reviews, publishing, and patents - Define the science strategy for how we help authors publish, grow, and succeed, balancing near-term launches with long-term bets - Partner with engineering, product, and policy teams to take science from prototype to production and measure its impact on authors - Write design and planning documents for your area, and present options, risks, and tradeoffs to senior leaders so they can decide - Work closely with our scientists in the US to deliver faster for our authors and improve their experience with our services About the team Kindle Direct Publishing (KDP) lets anyone publish a book. We are the science organization for Amazon's Books business, now building our science teams in Bengaluru. Our team works in three connected areas: a support assistant that answers authors' questions from their own account data, in every language KDP supports; multimodal models that use book attributes to keep the catalog trustworthy and help authors reach the right readers; and fine-tuned models that power the assistant and catalog models with KDP expertise. We serve authors, from first-time writers to full-time publishers. We value safety before speed and shared foundations over one-off fixes. Scientists here get dedicated time for innovation, which can lead to patents and conference papers.
Applied Scientist
IN, KA, Bengaluru
Help millions of authors around the world get their books published, discovered, and supported. As one of the first scientists on our new team in Bengaluru, you'll help turn ideas into models authors rely on every day, building agentic solutions with large language models (LLMs), multimodal models, and fine-tuning. Key job responsibilities - Build the multi-agent system behind KDP's author support assistant: orchestration across specialized agents and tools, personalization, and the evaluation that drives its continuous improvement. - Build multimodal models of book attributes, and use them for similar-book search across languages, catalog quality, and category and keyword recommendations. - Post-train open models on KDP expertise (for example with supervised fine-tuning and reinforcement learning), and deploy them where they beat general-purpose models on accuracy, cost, or speed. - Work closely with our scientists in the US and with engineering partners to take your work to production, design rigorous offline and online experiments, and write clear readouts with recommendations. About the team Kindle Direct Publishing (KDP) lets anyone publish a book. We are the science organization for Amazon's Books business, now building our science teams in Bengaluru. Our team works in three connected areas: a support assistant that answers authors' questions from their own account data, in every language KDP supports; multimodal models that use book attributes to keep the catalog trustworthy and help authors reach the right readers; and fine-tuned models that power the assistant and catalog models with KDP expertise. We serve authors, from first-time writers to full-time publishers. You will work closely with engineering, product, and policy partners. We value safety before speed and shared foundations over one-off fixes. Scientists here get dedicated time for innovation, which can lead to patents and conference papers.
Senior Applied Scientist, Computer Vision and Robotics, Amazon Robotics
US, MA, North Reading
Come shape the future of robotic sensing hardware by building the computer vision and ML systems that define how every robot in Amazon's global fulfillment network sees, senses, and understands the world. This is applied science embedded in a hardware development team where you directly shape what gets built, manufactured, and deployed at scale. As a Senior Applied Scientist on the Amazon Robotics Sensing and Compute hardware team, you will be the ML and perception expert working alongside the Principal Applied Scientist and Principal Hardware Development Engineer to shape the future of deployed and scaled sensing hardware. You will influence sensor selection, compute architecture, optical design, and system level trade offs, ensuring the hardware we build is purpose designed for the algorithms that run on it. You will help define what the next generation of cameras, depth sensors, and edge compute modules need to be, and then prove it with data, experimentation, and production validation. What makes this role unique: -Embedded in the hardware development team, directly influencing what gets designed, manufactured, and shipped -Partner with the Principal Engineers to co define the sensing and compute hardware roadmap for every major Amazon Robotics program -Own the ML experimentation and validation that drives hardware architecture decisions for cameras, depth sensors, and edge compute -Solve perception problems no other company is tackling: safety rated vision, multi modal sensor fusion, and real time inference on resource constrained hardware -Ship to hundreds of fulfillment sites worldwide across autonomous mobile robots, manipulation workcells, barcode sensing, and safety rated human collaborative systems -Your work does not sit in a research queue. It goes into production hardware that enables the future of Amazon Robotics Key job responsibilities -Partner with the Principal Hardware Development Engineer and Principal Applied Scientist to co define sensing and compute hardware requirements, ensuring ML and perception needs drive sensor selection, optical design, compute architecture, and system level trade offs -Develop and optimize computer vision and deep learning models for robotic perception including object detection, depth estimation, scene understanding, and barcode recognition, purpose built for edge deployment on resource constrained hardware -Lead ML experimentation and validation that directly informs hardware architecture decisions for cameras, depth sensors, and edge compute modules -Design and execute benchmarking frameworks to evaluate sensing hardware performance across diverse robotic use cases, providing data driven recommendations on what to build next -Optimize models for production edge deployment including quantization, pruning, distillation, and inference pipeline tuning to meet strict latency, power, and accuracy requirements -Drive research and experimentation on next generation perception capabilities in collaboration with the Principal Applied Scientist, including multi modal sensor fusion, safety rated vision, and real time inference for autonomous and human collaborative robotics -Collaborate cross functionally with hardware engineers, software developers, and robotics program teams to transition models from prototype through production validation and fleet deployment -Contribute to the sensing and compute hardware roadmap alongside the Principal Applied Scientist, identifying where ML trends and emerging capabilities require new hardware architecture or sensor modalities -Mentor engineers and scientists on ML best practices for embedded systems and production robotics -Publish and present research to advance the state of the art in robotic perception A day in the life In this role you will work at the intersection of machine learning and physical robotics hardware. You will collaborate with hardware engineers to evaluate how your models perform on real sensors and edge compute, run experiments that directly influence what gets built next, and validate perception systems alongside robotics program teams. You will push the boundaries of computer vision for robotic applications while seeing your work deploy on real robots in real fulfillment centers. This is applied science with immediate, measurable impact at a scale no other robotics company can offer. Amazon offers a full range of benefits that support you and eligible family members, including domestic partners. 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: 1. Medical, Dental, and Vision Coverage 2. Maternity and Parental Leave Options 3. Paid Time Off (PTO) 4. 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 Amazon Robotics Sensing and Compute team powers a customer centric ecosystem built for speed, quality, and innovation. We stay ahead of sensing and compute technology, standardize reusable and cost effective modules, and pair them with deep engineering expertise and a robust supply chain. Every customer gets the right solution, whether off the shelf, rapidly customized, or purpose built, easy to integrate and ready to scale. We are a small, fast moving team of builders who own the full stack from optics through edge compute and take pride in shipping production hardware that enables every major robotics program in Amazon's global fulfillment network. If you want your work to matter on day one, this is the team.
Sr. Applied Scientist - CV, Vulcan Stow
US, WA, Seattle
Do you want to create the greatest-possible worldwide impact in Robotics? Amazon has the world's most exciting treasure trove of robotics challenges. At Amazon Robotics we build high-performance, real-time robotic systems that can perceive, learn, and act intelligently alongside humans—at Amazon scale. Amazon Robotics invents and scales AI systems for robotics in fulfillment. Our mission is to enable robots to interact safely, efficiently, and fluently high density real-world fulfillment centers. Our AI solutions enable robots to learn from their own experiences, from each other, and from humans to build intelligence that feeds itself. We hire and develop subject matter experts in AI with a focus on 3D perception, computer vision, deep learning, and generative modeling. We target high-impact algorithmic unlocks in areas such as 3D scene understanding and completion, semantic occupancy prediction, multi-view 3D reconstruction, depth estimation, shape completion, and real-time inference - all of which have high-value impact for our current and future fulfillment networks. We are seeking an passionate, hands-on, seasoned Senior Applied Scientist who will be deep in code and algorithms; who is technically strong in building scalable 3D perception systems across semantic scene completion, encoder-decoder and transformer architectures (e.g., VoxFormer, MonoScene), voxelized occupancy prediction, panoptic and instance segmentation, depth estimation, point cloud processing, and multi-view fusion. As a Senior Applied Scientist, you will contribute to the research and development of advanced 3D perception pipelines that enable robots to reason about occluded and partially observed environments; your work along with other top-notch scientists and engineers will deliver the world's most scalable and robust robotic perception systems. You will drive ideas to products using paradigms such as 3D generative models, query-based transformers, masked autoencoder-style completion, and scalable pseudo-ground-truth data generation. As a Senior Applied Scientist, you will also help lead and mentor our team of applied scientists and engineers. You will take on challenging perception problems - such as completing 3D bin scenes from partial observations, integrating multi-camera inputs, and optimizing inference latency for edge deployment - distill requirements, and then deliver solutions that either leverage existing academic and industrial research or utilize your own out-of-the-box but pragmatic thinking. In addition to coming up with novel solutions and prototypes, you will directly contribute to implementation while you lead. A successful candidate has excellent technical depth in 3D computer vision, scientific vision, project management skills, great communication skills, and a drive to achieve results in a collaborative team environment. You should enjoy the process of solving real-world problems that, quite frankly, haven't been solved at scale anywhere before. Along the way, we guarantee you'll get opportunities to be a disruptor, prolific innovator, and a reputed problem solver—someone who truly enables AI and robotics to significantly impact the lives of millions of consumers. Key job responsibilities Architect, design, and implement 3D perception models - including encoder-decoder networks, query-based transformers, and generative architectures- for semantic occupancy prediction and scene completion on robotic platforms. Own the end-to-end model lifecycle: develop scalable training pipelines, optimize inference latency for ARM-based edge processors, and deploy production models that meet real-time performance targets. Design and scale pseudo-ground-truth data generation pipelines - both heuristic-based and learning-based (e.g., SAM3D, shape completion) to produce curated training samples using SageMaker infrastructure. Drive multi-view perception integration by fusing multiple view camera inputs for robust 3D reconstruction in partially observed and occluded bin environments. Influence the team's technical strategy and contribute to the long-term vision and roadmap for 3D perception in fulfillment robotics. Partner with cross-functional stakeholders across engineering, science, and operations teams to define requirements, iterate on system design, and deliver end-to-end solutions from research prototype to production deployment. Maintain high standards by participating in design and code reviews, designing for fault tolerance and operational excellence, and creating mechanisms for continuous improvement. Prototype and validate concepts through simulation, synthetic data evaluation, and live robotic workcell testing using 3D metrics (mIoU, IoU) and affordance-based evaluation frameworks. Mentor applied scientists and engineers, raise the technical bar, and foster a culture of scientific rigor and rapid experimentation. A day in the life Amazon offers a full range of benefits that support you and eligible family members, including domestic partners. 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: 1. Medical, Dental, and Vision Coverage 2. Maternity and Parental Leave Options 3. Paid Time Off (PTO) 4. 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!
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