AI for Information Security call for proposals — Fall 2024

Advancing possible solutions for some of the most challenging problems in information security.

About this CFP

AWS is committed to helping customers achieve the highest levels of security in the cloud. Our security services use cutting-edge machine learning algorithms to improve the security posture of AWS accounts. We aim to continue advancing possible solutions for some of the most challenging problems in information security. We are seeking to fund machine learning research on the following topics in information security:

  • Threat, intrusion, and anomaly detection for cloud security
  • Generative AI and foundation models for information security
  • Graph modeling and anomaly detection on graphs
  • Learning with limited/noisy labels and weakly supervised learning
  • ML for malware analysis and detection, with a focus on cloud environments or devices
  • Finding security vulnerabilities using ML
  • Causal inference for information security
  • Zero/one-shot learning for information security
  • Reinforcement learning for information security
  • Protecting and preserving data privacy in the cloud
  • Securing generative AI and foundation models

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 $40,000 USD on average

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.

Selection criteria

AI for Information Security will make the funding decisions based on the potential impact to the research community and quality of the scientific content.

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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Amazon Advertising drives billions of ad impressions and millions of clicks daily, powering discovery and sales for advertisers across Amazon's Retail and Marketplace businesses. The Ads Marketing Decision Science team sits at the intersection of data science and marketing strategy. We build intelligent, data-driven systems that analyze advertiser behavior at large scale to deliver the right guidance to the right advertiser at the right time. Our work spans behavioral modeling, content intelligence, automated decision systems, and GenAI applications, enabling personalized marketing experiences that help advertisers make smarter advertising decisions and grow their business on Amazon. We are looking for a Data Scientist who brings strong fundamentals in machine learning, causal inference, and statistical modeling to solve real advertiser problems. You will build predictive models, design experiments, develop segmentation frameworks, and leverage GenAI capabilities where applicable, taking solutions end-to-end from proof-of-concept to production at scale. You will partner closely with scientists, engineers, and product managers on a daily basis to prototype rapidly, ensure data integrity in production systems, and deliver measurable advertiser impact. If you are passionate about solving real-world problems with next level science, come join us as we innovate and make history. Key job responsibilities • Define and execute data science solutions end-to-end, from problem framing through production deployment. • Build machine learning models (classification, regression, clustering, ranking) for advertiser segmentation, propensity modeling, and recommendations. • Apply causal inference and experimentation methods (A/B testing, difference-in-differences, propensity score matching) to measure the impact of marketing interventions. • Analyze large-scale advertiser behavioral data to identify trends, surface growth opportunities, and support optimal decision making. • Collaborate with colleagues across science and engineering disciplines for fast turnaround proof-of-concept prototyping at scale. • Establish and drive data hygiene best practices to ensure coherence and integrity of data feeding into production ML/AI solutions. • Leverage GenAI and LLM capabilities to enhance science products where applicable A day in the life You will solve real-world problems by analyzing large volumes of advertiser data, building predictive models, designing experiments, and measuring business impact. You will prototype rapidly, validate ideas with data, and partner with engineers to productize and scale successful solutions. You will collaborate daily with scientists, engineers, and product managers across the advertising organization, working in a cross-functional, fast-paced environment where data drives decisions and helps advertisers grow. About the team We are a team of Applied Scientists, Research Scientists, Data Scientists, and Business Intelligence Engineers with deep expertise in ML, NLP, Gen-AI, RL, and causal inference, from a diverse range of backgrounds. We partner closely with strong engineers, product managers, and sales leaders who bring ads-industry depth and experience building scalable modeling and software solutions.
GB, London
We're building systems that turn research into real-world impact — ensuring flawless streaming for millions of Prime Video customers, shaping the future of AI-driven shopping with Rufus, advancing speech generation and conversational AI, optimizing large-scale infrastructure through intelligent observability, and transforming how people and jobs find each other. If this sounds interesting to you then we have a range of opportunities for you to explore. We're looking for PhD students across multiple research domains to invent, design, and implement state-of-the-art solutions for never-before-solved problems. Your work here won't just stay in a notebook — it ships to production and reaches customers worldwide. Check out the details below including the job responsibilities, team details, and basic qualifications before submitting your application. You can find more information about the Amazon Science community as well as interview preparation tips via the links below; - https://www.amazon.science/ - https://amazon.jobs/content/en/career-programs/university/science - https://amazon.jobs/content/en/how-we-hire/university-roles/applied-science Key job responsibilities As an Applied Science Intern, you will own the design and development of end-to-end systems. You'll have the opportunity to write technical white papers, create roadmaps and drive production level projects that will support Amazon Science. You will work closely with Amazon scientists and other science interns to develop solutions and deploy them into production. You will have the opportunity to design new algorithms, models, or other technical solutions whilst experiencing Amazon's customer focused culture. The ideal intern should have the ability to work with diverse groups of people and cross-functional teams to solve complex business problems. A day in the life You'll spend your first weeks scoping your project with your mentor, then own the research and implementation end-to-end. Your work could involve building computer vision models that detect quality issues across Prime Video's content library, developing multimodal AI solutions that power Amazon's shopping assistant Rufus, creating automated reasoning tools that verify distributed systems at scale, engineering intelligent observability frameworks for large-scale infrastructure, or advancing recommendation models that connect people with the right jobs — depending on the team you're matched with. Many interns publish at top-tier conferences or see their work deployed to production before the internship ends. Interns may also be considered for a return offer at the end of their internship, subject to performance evaluation and headcount availability. Further benefits of an Amazon Science internship include; - All of our internships offer a competitive salary - Interns are paired with an experienced manager and mentor(s) - Interns get invited to different intern program or office events - Interns can build their professional and personal network with other Amazon Scientists - Interns can potentially publish work at top tier conferences About the team We're hiring interns for multiple teams in the UK, including but not limited to; • Prime Video Video Quality Analysis – Develops AI and machine learning solutions using computer vision, audio processing, and generative AI to detect and prevent streaming quality issues across Prime Video's vast content library • Rufus Features Science UK – Shapes AI-driven shopping experiences at Amazon, working on projects from enabling Rufus to take actions on behalf of customers to generating multimodal answers combining text, image, audio, and video. • READI – Observability, Triage & Peak Readiness – Builds intelligent log analytics and automated performance frameworks that transform system telemetry into actionable insights for large-scale distributed systems. • Automated Reasoning Group – Ensures program and systems correctness through deductive proof, model checking, formal verification, and runtime conformance monitoring for large-scale distributed systems. You'll submit a single application and we'll match you with science teams best aligned with your research interests. Applications are reviewed on a rolling basis, and your application stays active until we find a team match or confirm there are no matches available. Start dates are available throughout the year for durations of between 3–6 months. Please note, each team has different start date and duration preferences — your recruiter will confirm the preferences of the team you're matched with prior to interviewing. We offer science internships in multiple locations across the EMEA region and you can indicate your interest in all these locations by applying here (Austria, Estonia, France, Germany, Ireland, Israel, Italy, Jordan, Luxembourg, Netherlands, Poland, Romania, South Africa, Spain, Sweden, UAE, and UK). Please note we do not offer remote internships.
IL, Tel Aviv
We're building systems that turn research into real-world impact — powering sports experiences for millions of Prime Video customers, pioneering multimodal document intelligence, building autonomous AI agents that reason, plan, and act, and transforming how customers discover products they love. If this sounds interesting to you then we have a range of opportunities for you to explore. We're looking for PhD students across multiple research domains to invent, design, and implement state-of-the-art solutions for never-before-solved problems. Your work here won't just stay in a notebook — it ships to production and reaches customers worldwide. Check out the details below including the job responsibilities, team details, and basic qualifications before submitting your application. You can find more information about the Amazon Science community as well as interview preparation tips via the links below; - https://www.amazon.science/ - https://amazon.jobs/content/en/career-programs/university/science - https://amazon.jobs/content/en/how-we-hire/university-roles/applied-science Key job responsibilities As an Applied Science Intern, you will own the design and development of end-to-end systems. You'll have the opportunity to write technical white papers, create roadmaps and drive production level projects that will support Amazon Science. You will work closely with Amazon scientists and other science interns to develop solutions and deploy them into production. You will have the opportunity to design new algorithms, models, or other technical solutions whilst experiencing Amazon's customer focused culture. The ideal intern should have the ability to work with diverse groups of people and cross-functional teams to solve complex business problems. A day in the life You'll spend your first weeks scoping your project with your mentor, then own the research and implementation end-to-end. Your work could involve building computer vision models that power live sports experiences for Prime Video, developing multimodal GenAI solutions for AWS document intelligence, creating agentic AI systems that reason and act autonomously, or advancing recommendation models that transform how customers discover content — depending on the team you're matched with. Many interns publish at top-tier conferences or see their work deployed to production before the internship ends. Interns may also be considered for a return offer at the end of their internship, subject to performance evaluation and headcount availability. Further benefits of an Amazon Science internship include; - All of our internships offer a competitive salary - Interns are paired with an experienced manager and mentor(s) - Interns get invited to different intern program or office events - Interns can build their professional and personal network with other Amazon Scientists - Interns can potentially publish work at top tier conferences About the team We're hiring interns for multiple teams in Israel, including but not limited to; • Prime Video Sports — Build innovative sports experiences for Prime Video, spanning computer vision, 3D simulation, and personalized content recommendations. • Personalization — Leverage LLMs, NLP, and recommender systems to match customers with products that align with their passions and shopping preferences. • Agentic AI — Build next-generation agentic AI systems that automate real-world knowledge work, spanning retrieval-augmented generation, multi-agent workflows, long-term memory and personalization, knowledge-graph construction, and agent evaluation. • DS3 Textract — Develop multimodal generative AI algorithms that pioneer state-of-the-art document understanding solutions impacting millions of customers. You'll submit a single application and we'll match you with science teams best aligned with your research interests. Applications are reviewed on a rolling basis, and your application stays active until we find a team match or confirm there are no matches available. Start dates are available throughout the year. Some teams offer full-time internships (3–6 months) while others offer part-time positions (50–60%, 8–12 months) — your recruiter will confirm the format during team matching. We offer science internships in multiple locations across the EMEA region and you can indicate your interest in all these locations by applying here (Austria, Estonia, France, Germany, Ireland, Israel, Italy, Jordan, Luxembourg, Netherlands, Poland, Romania, South Africa, Spain, Sweden, UAE, and UK). Please note we do not offer remote internships.
ES, Madrid
We're building the intelligence behind how customers discover, trust and enjoy products on Amazon. We're solving complex catalogue quality challenges with machine learning, enhancing product discovery through computer vision and multimodal AI and pioneering agentic systems that autonomously navigate and stress-test the Amazon shopping experience to surface insights at scale. We're looking for PhD students across multiple research domains to invent, design, and implement state of the art solutions for never before solved problems. Your work here won't just stay in a notebook, it ships to production and reaches customers worldwide. Check out the details below including the job responsibilities, team details, and basic qualifications before submitting your application. You can find more information about the Amazon Science community as well as interview preparation tips via the links below; - https://www.amazon.science/ - https://amazon.jobs/content/en/career-programs/university/science - https://amazon.jobs/content/en/how-we-hire/university-roles/applied-science Key job responsibilities As an Applied Science Intern, you will own the design and development of end-to-end systems. You'll have the opportunity to write technical white papers, create roadmaps and drive production level projects that will support Amazon Science. You will work closely with Amazon scientists and other science interns to develop solutions and deploy them into production. You will have the opportunity to design new algorithms, models, or other technical solutions whilst experiencing Amazon's customer focused culture. The ideal intern should have the ability to work with diverse groups of people and cross-functional teams to solve complex business problems. A day in the life You'll spend your first weeks scoping your project with your mentor, then own the research and implementation end-to-end. Your work could involve developing machine learning and data analysis solutions that detect and resolve catalogue quality issues at massive scale, building computer vision and multimodal learning models that transform how customers discover and interact with products, engineering universal ML systems that make shopping on Amazon easier and more visually delightful, or creating autonomous agentic shoppers that tirelessly navigate the Amazon website to provide feedback and actionable insights — depending on the team you're matched with. Many interns publish at top-tier conferences or see their work deployed to production before the internship ends. Interns may also be considered for a return offer at the end of their internship, subject to performance evaluation and headcount availability. Further benefits of an Amazon Science internship include; - All of our internships offer a competitive salary - Interns are paired with an experienced manager and mentor(s) - Interns get invited to different intern program or office events - Interns can build their professional and personal network with other Amazon Scientists - Interns can potentially publish work at top tier conferences About the team We're hiring interns for multiple teams in Spain including but not limited to; •Tamale - Using Machine Learning and Data analysis solutions to solve complex catalogue quality problems • NintAI- Developing AI solutions, focusing on computer vision and multimodal learning to enhance how customers discover and interact with products • Home Innovation tech- Building universal, state of the art Machine Learning technology that makes shopping on Amazon easier and more visually delightful for our customers • EU Intech- Pioneers a population of agentic shoppers, autonomous AI agents, that tirelessly navigate and shop on the Amazon website, providing feedback and insights to improve the customer experience You'll submit a single application and we'll match you with science teams best aligned with your research interests. Applications are reviewed on a rolling basis, and your application stays active until we find a team match or confirm there are no matches available. Start dates are available throughout the year for durations of between 3–6 months. Please note, each team has different start date and duration preferences — your recruiter will confirm the preferences of the team you're matched with prior to interviewing. We offer science internships in multiple locations across the EMEA region and you can indicate your interest in all these locations by applying here (Austria, Estonia, France, Germany, Ireland, Israel, Italy, Jordan, Luxembourg, Netherlands, Poland, Romania, South Africa, Spain, Sweden, UAE, and UK). Please note we do not offer remote internships.
US, CA, Sunnyvale
We are seeking an Applied Scientist to focus on Robot Navigation. In this role, you'll research and develop advanced navigation systems that enable robots to move reliably and safely through complex, dynamic environments. You'll work across a broad spectrum of navigation approaches—from classical methods to learning-based techniques and foundation models—to build robust solutions for autonomous robot navigation. Key job responsibilities - Develop and implement robust navigation systems that enable reliable autonomous operation in complex, dynamic indoor environments with static and dynamic obstacles - Build simulation-based and on-device evaluation frameworks with comprehensive benchmarks and metrics for systematic comparison of navigation methods - Conduct sim-to-real transfer experiments, analyzing performance gaps and developing techniques to ensure reliable real-world navigation performance - Collaborate with world model, manipulation, and other teams to ensure seamless integration of navigation capabilities into the full robot system - Stay current with the latest advances in robot navigation, spatial reasoning, and related fields, and apply relevant findings to improve system performance - Mentor fellow scientists and engineers while maintaining strong individual technical contributions 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.
US, CA, Sunnyvale
Are you a passionate scientist who wants to build AI agents that make a real difference in people's lives? At Ring, our mission is to make neighborhoods safer, and we believe agentic AI will change how customers interact with their homes and communities. You'll invent agents that reason about real-world situations, take meaningful action, and keep customers in control, and then you'll see them reach millions of households. As an Applied Scientist, you'll work with talented peers to push the frontier of agentic AI. You'll build agents that turn the multimodal signals captured by Ring devices into understanding and action. You'll tackle open problems in planning, tool use, learning from feedback, and reliability, taking ideas from research all the way to deployment at scale. You'll collaborate with teams across Amazon to advance the science of customer experiences through highly optimized, integrated hardware and software platforms. Key job responsibilities - Design, develop, and deploy LLM-based agents that plan and carry out multi-step tasks for customers using tools, services, and device data. - Advance the state of the art in agent capabilities such as planning, tool use, memory, and learning from feedback (e.g., RL and agent fine-tuning), and publish where appropriate. - Partner with engineering, product, and science teams to turn research into agent-driven experiences that help keep homes and neighborhoods safer.
US, WA, Seattle
We are seeking a Senior Applied Scientist to join our team in developing pioneering AI research, Generative AI, Agentic AI, Large Language Models (LLMs), Diffusion and Flow Models, and other advanced Machine Learning and Deep Learning solutions for Amazon Selection and Catalog Systems, within the AI Lab Team. This role offers a unique opportunity to work on AI research and AI products that will shape the future of online shopping experiences. Our team operates at the forefront of AI research and development, working on challenges that directly impact millions of customers worldwide. We push the boundaries of AI at both the foundational and application layers. As a Senior Applied Scientist, you will have the chance to experiment with LLMs and deep learning techniques, apply your research to solve real-world problems at an unprecedented scale, and collaborate with experienced scientists to contribute to Amazon's scientific innovation. Join us in redefining the future of shopping. Your work will directly influence how customers interact with the world's largest online store. Key job responsibilities - Design and implement novel AI solutions for Amazon catalog of products - Develop and train state-of-the-art LLMs, Diffusion Models, and other Generative AI models - Build and deploy autonomous AI Agents in Amazon production ecosystem - Scale AI models to handle billions of diverse products across multiple languages and geographies - Conduct research in areas such as Autonomous AI Agents, Generative AI, Language Modeling, Multi-modality Computer Vision, Diffusion Models, Reinforcement Learning - Collaborate with cross-functional teams to integrate AI models into Amazon's production ecosystem - Contribute to the scientific community through publications and conference presentations
US, NY, New York
We are seeking a Senior Applied Scientist to lead research and development of novel security validation and monitoring techniques for AI systems at scale. You will own and contribute to four critical workstreams: 1. Real-Time Agent Monitoring Design and implement scientific approaches for continuous behavioral analysis of AI agents in production—detecting anomalous actions, prompt injection exploitation, and policy violations in real time. 2. MCP Server Validation Develop novel validation frameworks to assess the security posture of Model Context Protocol (MCP) servers, including input sanitization verification, tool-use authorization boundaries, and data exfiltration detection. 3. AI-Enabled Application Validation Invent and deliver scalable methodologies for security testing of AI-enabled applications, including adversarial robustness evaluation, safety guardrail bypass detection, and trust boundary verification. 4. AI Asset Discovery & Inventory Research and build scalable techniques to automatically discover, identify, and catalog all AI-enabled applications and services across the company—maintaining a comprehensive, continuously updated database of AI assets. Key job responsibilities Invent • Identify and frame new research challenges in AI security where problems are ill-defined and require novel scientific paradigms at the product level. • Drive the team's scientific agenda for agent monitoring, validation research, and AI asset discovery; propose new initiatives and secure leadership buy-in. • Publish research results at peer-reviewed internal and external venues (e.g., USENIX Security, IEEE S&P, NeurIPS, ICML security workshops) when appropriate. • Articulate key scientific challenges of current and future AI security threats and present interventions to address them. • Make trade-offs between short-term tactical security needs and long-term research investments. Implement • Lead the design, implementation, and successful delivery of scientifically complex security solutions into production—both brand new systems and evolutions of existing ones. • Write significant portions of critical-path code for detection models, validation engines, and asset discovery / classification systems. • Independently assess and select appropriate technologies (e.g., streaming inference frameworks, graph-based anomaly detection, NLP-based service classification, code/traffic analysis for AI fingerprinting) for production systems. • Drive adoption of best practices in scientific methodology and software engineering across the team; provide insightful peer reviews of code, design, and architecture artifacts. • Deliver solutions that are inventive, maintainable, scalable, and extensible. Influence • Autonomously drive discussions with security engineers, product managers, and scientist peers across multiple teams. • Build consensus on larger cross-team security initiatives and factor complex efforts into independent workstreams. • Proactively identify and resolve endemic problems, including areas where current security tooling limits innovation of partner teams. • Actively recruit, mentor, and develop other scientists; provide technical assessments for promotions. • Contribute to the broader internal and external scientific communities as a subject matter expert in AI security. About the team Diverse Experiences Amazon Security values diverse experiences. Even if you do not meet all of the qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying. Why Amazon Security? At Amazon, security is central to maintaining customer trust and delivering delightful customer experiences. Our organization is responsible for creating and maintaining a high bar for security across all of Amazon’s products and services. We offer talented security professionals the chance to accelerate their careers with opportunities to build experience in a wide variety of areas including cloud, devices, retail, entertainment, healthcare, operations, and physical stores. Inclusive Team Culture In Amazon Security, it’s in our nature to learn and be curious. Ongoing DEI events and learning experiences inspire us to continue learning and to embrace our uniqueness. Addressing the toughest security challenges requires that we seek out and celebrate a diversity of ideas, perspectives, and voices. Training & Career Growth We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, training, and other career-advancing resources here to help you develop into a better-rounded professional. Work/Life Balance We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why flexible work hours and arrangements are part of our culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve.
US, WA, Seattle
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 add-on subscriptions such as Apple TV+, Max, 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 technologist, 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! The Prime Video Title Lifecycle Presentation team sits at the intersection of science, experimentation, and customer experience. We leverage data signals and rigorous testing to present the most engaging information about our content to customers at precisely the right moment. Our mission is to ensure every customer interaction with Prime Video content is informed, relevant, and compelling in order to drive discovery and engagement across our vast catalog. We're seeking a Sr. Applied Scientist who excels at building sophisticated machine learning systems for content presentation and discovery. The ideal candidate brings deep expertise in: - Multi-modal embeddings for rich metadata representation, enabling nuanced understanding of content attributes and customer preferences - Contextualized ranking systems that adapt to customer intent, viewing context, and real-time signals - Reinforcement learning frameworks that create continuous improvement loops, allowing our systems to learn and optimize from customer interactions over time - General modeling techniques with strong fundamentals in machine learning and statistical methods - Recommender systems experience, with proven ability to build and scale personalization solutions You'll work with technology to solve complex problems in content discovery, leveraging large-scale data to create experiences that delight millions of Prime Video customers worldwide. Key job responsibilities - Lead Cross-Functional Science Initiatives: Drive a diverse portfolio of applied science projects spanning recommender systems, generative AI agent development and evaluation across multiple modalities, and computer vision applications. Demonstrate both breadth of understanding across technical domains and sufficient depth in each area to effectively lead multiple concurrent initiatives to successful outcomes. - Bridge Science and Engineering for Production-Scale Deployment: Partner with engineering teams to productionize machine learning models at Prime Video scale. Develop production-ready science code that meets engineering standards for performance, reliability, and maintainability, ensuring seamless transition from research to deployment. - Mentor and Develop Technical Talent: Provide technical mentorship and guidance to junior scientists and engineers on applied science methodologies, best practices, and professional development. Foster a culture of scientific rigor and continuous learning within the team.
US, MA, N.reading
Amazon is seeking exceptional talent to help develop the next generation of advanced robotics systems that will transform automation at Amazon's scale. We're building revolutionary robotic systems that combine cutting-edge AI, sophisticated control systems, and advanced mechanical design to create adaptable automation solutions capable of working safely alongside humans in dynamic environments. This is a unique opportunity to shape the future of robotics and automation at an unprecedented scale, working with world-class teams pushing the boundaries of what's possible in robotic dexterous manipulation, locomotion, and human-robot interaction. This role presents an opportunity to shape the future of robotics through innovative applications of deep learning and large language models. At Amazon we leverage advanced robotics, machine learning, and artificial intelligence to solve complex operational challenges at an unprecedented scale. Our fleet of robots operates across hundreds of facilities worldwide, working in sophisticated coordination to fulfill our mission of customer excellence. The ideal candidate will contribute to research that bridges the gap between theoretical advancement and practical implementation in robotics. You will be part of a team that's revolutionizing how robots learn, adapt, and interact with their environment. Join us in building the next generation of intelligent robotics systems that will transform the future of automation and human-robot collaboration. Key job responsibilities - Design and implement whole body control methods for balance, locomotion, and dexterous manipulation - Utilize state-of-the-art in methods in learned and model-based control - Create robust and safe behaviors for different terrains and tasks - Implement real-time controllers with stability guarantees - Collaborate effectively with multi-disciplinary teams to co-design hardware and algorithms for loco-manipulation - Mentor junior engineer and scientists
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Amazon Research Awards

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