Amazon Research Awards - AI/ML Focus is sponsored by Amazon. Provides unrestricted funding gifts to academic researchers working on industry-scale technical challenges, with a particular focus on artificial intelligence and machine learning.

Call For Proposals | Amazon Research Awards - Amazon Science Information and knowledge management Operations research and optimization Security, privacy, and abuse prevention Our scientific contributions Research from our scientists and collaborators. Our experts present and discuss cutting-edge research at scientific meetings globally.

Information and knowledge management Operations research and optimization Security, privacy, and abuse prevention Our scientific contributions Research from our scientists and collaborators. Our experts present and discuss cutting-edge research at scientific meetings globally. The latest from Amazon researchers Technical deep-dives and perspectives from our scientists.

Research milestones and recent achievements. The latest from Amazon researchers Technical deep-dives and perspectives from our scientists. Research milestones and recent achievements.

Carnegie Mellon University Tennessee State University University of California, Los Angeles University of Illinois Urbana-Champaign University of Southern California University of Texas at Austin Carnegie Mellon University Tennessee State University University of California, Los Angeles University of Illinois Urbana-Champaign University of Southern California University of Texas at Austin Meet the team building useful AI agents.

Try Amazon’s frontier foundation models. Meet the team building useful AI agents. Try Amazon’s frontier foundation models.

Faculty research opportunities on industry-scale technical challenges. Postdoctoral Science Program Early-career research opportunities alongside experienced industry scientists. Faculty research opportunities on industry-scale technical challenges.

Postdoctoral Science Program Early-career research opportunities alongside experienced industry scientists. Awards are structured as unrestricted gifts to the principal investigator's academic institution or organization and as such, Amazon retains no intellectual property rights to the resulting work. Recipients are encouraged to publish outcomes and commit related code to open-source repositories.

Recipients are assigned an Amazon research contact who offers consultation and advice along with opportunities to participate in Amazon events and training sessions. The submission period has been extended to May 13.

AI for Information Security Advancing possible solutions for some of the most challenging problems in information security Advancing the frontiers of AI agents Advancing science through scale-driven innovation in the next three to five years Setting the standard for security at Amazon Build on Trainium: Accelerating Post-Training Building the future of AI with AWS Trainium Build on Trainium: Kernels for ML Acceleration Building the future of AI with AWS Trainium Pursuing the future of robotics research The submission period closed on November 12.

AI for Information Security Advancing possible solutions for some of the most challenging problems in information security. Advancing the frontiers of AI agents Systems assurance by mathematical proof.

Build on Trainium: Responsible AI Building the future of AI with AWS Trainium Setting the standard for cryptography at Amazon Cybersecurity and Anti-Abuse Technologies Advancing solutions to protect the Web from sophisticated cybercrime, abuse and fraud at scale Data-driven solutions for Devices Sustainability: Optimizing manufacturing and use phase impact Advancing the frontiers of science through transformative ideas The submission period closed on May 7.

AI for Information Security Advancing possible solutions for some of the most challenging problems in information security. Advancing customer protections in the era of artificial intelligence in digital advertising. Advancing the frontiers of AI.

Building the future of AI with AWS Trainium. Advancing the frontiers of science through transformative ideas. The submission period closed on November 13.

AI for Information Security Advancing possible solutions for some of the most challenging problems in information security. Systems assurance by mathematical proof. Advancing the frontiers of machine learning.

Setting the standard for cryptography at Amazon. Welcoming proposals related to data validation, life cycle assessment, biodiversity and more. The submission period closed on May 7.

AI for Information Security Advancing possible solutions for some of the most challenging problems in information security. Addressing the challenges associated with generating consistent, transparent, and accurate carbon measurements. The submission period closed on March 6.

Foundation Model Development Advancing the frontiers of foundation model development. The submission period closed on November 13. Decision letters were sent out March 2024.

AI for Information Security Helping customers achieve the highest levels of security in the cloud. Systems assurance by mathematical proof Advancing the frontiers of machine learning. AWS Cryptography and Privacy Setting the standard for cryptography and privacy at Amazon.

Innovative approaches to designing, building, or operating large-scale database services or distributed cloud services. Making Amazon the most environmentally and socially responsible place to buy or sell goods and services. The submission period closed April 26.

Decision letters were sent out August 2023. AWS AI solicited funding proposals related to generative AI, which focused on innovation related to supporting annotators with machine learning and artificial intelligence. The submission period closed October 26.

Decision letters were sent March 2023. Advancing the frontiers of machine learning. Systems assurance by mathematical proof Pushing the boundaries of science and technology Welcoming proposals related to climate risk/resilience, life cycle assessment, circular strategies, and more.

The submission period closed July 15. Decisions letters were sent December 2022.

AI for Information Security Advancing cybersecurity with AI Amazon Science Community and Machine Learning University Making Amazon the best place in the world to do customer-obsessed science and engineering Breakthroughs in online advertising AWS AI: Human-in-the-loop machine learning and annotation Sharing learnings and ML capabilities as fully managed services The submission period closed January 21.

Decision letters were sent May 2022. The submission period closed October 8. Decision letters were sent March 2022.

AI for Information Security Advancing cybersecurity with AI Data for Social Sustainability Advancing the use of data science for social good Amazon Device Security and Privacy Enabling trustworthy compute environment from edge to cloud Breakthroughs in security, verification, and anomaly detection Advancing the frontiers of machine learning Security assurance, backed by mathematical proof Prime Video - Automating Quality Analysis & Delivery Solving audio/video challenges with machine learning Pursuing the future of robotics research Amazon Advertising - Summer 2021 Breakthroughs in online advertising Alexa Fairness in AI - Spring 2021 AWS Automated Reasoning - Spring 2021 Security assurance, backed by mathematical proof AI for Information Security - Fall 2020 Advancing cybersecurity with AI Alexa Fairness in AI - Fall 2020 Pursuing the future of robotics research Advancing the frontiers of machine learning AWS Automated Reasoning - Fall 2020 Security assurance, backed by mathematical proof Applied Scientist - Perception (SLAM/VIO), Fauna We are seeking an Applied Scientist to develop and optimize Visual Inertial Odometry (VIO) and sensor fusion systems for our intelligent robots.

In this role, you will design, implement, and deploy state estimation and tracking algorithms that enable robots to understand their position and motion in real time, even in challenging and dynamic environments. You will own the full pipeline from algorithm development through embedded deployment, ensuring that perception systems run efficiently on resource-constrained robotic hardware.

You will also leverage modern machine learning approaches to push the boundaries of classical perception methods, combining learned representations with geometric techniques to achieve robust, real-time performance. This is a deeply hands-on role. You will work directly with sensors, hardware, and real-world data, while prototyping, testing, and iterating in physical environments.

The ideal candidate has strong foundations in VIO and sensor fusion, practical experience optimizing algorithms for embedded platforms, and familiarity with how modern deep learning is transforming perception.

Key job responsibilities - Design and implement Visual Inertial Odometry algorithms for robust real-time state estimation on robotic platforms like Sprout - Develop multi-sensor fusion pipelines integrating cameras, IMUs, and other sensing modalities for accurate pose tracking - Optimize perception and tracking algorithms for deployment on embedded hardware (e.g., ARM, GPU-accelerated edge devices) under strict latency and power constraints - Apply modern ML-based perception techniques (learned features, depth estimation, neural odometry) to complement and improve classical geometric approaches - Build and maintain calibration, evaluation, and benchmarking infrastructure for perception systems - Collaborate with hardware, controls, and navigation teams to integrate perception outputs into the robot’s autonomy stack - Lead technical projects from research prototyping through production deployment Sr. Applied Scientist, Special Projects Innovators wanted!

Are you an entrepreneur? A builder? A dreamer?

This role is part of an Amazon Special Projects team that takes the company’s Think Big leadership principle to the limits. If you’re interested in innovating at scale to address big challenges in the world, this is the team for you. As an Applied Scientist on our team, you will focus on building state-of-the-art ML models for biology.

Our team rewards curiosity while maintaining a laser-focus in bringing products to market. Competitive candidates are responsive, flexible, and able to succeed within an open, collaborative, entrepreneurial, startup-like environment.

At the forefront of both academic and applied research in this product area, you have the opportunity to work together with a diverse and talented team of scientists, engineers, and product managers and collaborate with other teams.

Key job responsibilities - Build, adapt and evaluate ML models for life sciences applications - Collaborate with a cross-functional team of ML scientists, biologists, software engineers and product managers Economist III - AMZ9898444 MULTIPLE POSITIONS AVAILABLE Employer: AMAZON.

COM SERVICES LLC Offered Position: Economist III Job Location: Boston, Massachusetts Job Number: AMZ9898444 Position Responsibilities: Mentor and guide the applied scientists and economists in our organization and hold us to a high standard of technical rigor and excellence in science. Design and lead roadmaps for complex science projects to help SP have a delightful selling experience while creating long term value for our shoppers.

Work with our engineering partners and draw upon your experience to meet latency and other system constraints. Identify untapped, high-risk technical and scientific directions, and simulate new research directions that you will drive to completion and deliver. Be responsible for communicating our science innovations to the broader internal & external scientific community.

Position Requirements: Ph. D. or foreign equivalent degree in Economics or a related field and two years of research or work experience in the job offered or a related occupation.

Must have two years of research or work experience in the following skill(s): 1) experience in econometrics including experience with program evaluation, forecasting, time series, panel data, or high dimensional problems; 2) experience with economic theory and quantitative methods; and 3) coding in a scripting language such as R, Python, or similar. 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 $159,200/year to $215,300/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 Principal Applied Scientist, Automated Reasoning Group Sr. Research Scientist, Pricing Science Amazon's Worldwide Pricing & Promotions organization is seeking a talented, hands-on Research Scientist to join the Pricing and Promotion Optimization Science (P2OS) team — the optimization "application layer" within Amazon's Pricing Sciences organization.

Amazon adjusts prices on hundreds of millions of products daily across a global marketplace; P2OS is the team that makes those prices optimal. P2OS is a small, specialized unit with an outsized charter: develop and maintain the models that determine optimal prices and promotions across Amazon's catalog and merchant programs.

We own the full optimization stack — from price prediction to promotion targeting to competitiveness guardrails — and we measure success in terms of accretive Gross Contribution and Customer Pricing Perception (GCCP).

Our work spans Retail Core, Amazon Business, Fresh, Grocery, and international marketplaces, and we are continually investing in more extensible, generalizable science foundations to keep pace with a growing and evolving business.

We are looking for an innovative, organized, and customer-focused scientist with exceptional machine learning and predictive modeling skills, causal and experimental evaluation experience, and the entrepreneurial spirit to apply state-of-the-art methods to some of the most impactful pricing problems in e-commerce.

You should be comfortable with ambiguity, motivated by measurable business impact, and excited by the opportunity to work at Amazon-scale. Key job responsibilities * Innovate and build. Design, develop, and deploy machine learning models that set optimal prices and promotions across Amazon's global catalog.

Own models end-to-end — from problem formulation and data analysis through offline evaluation, A/B testing, and production launch. * Build a generalizable science foundation. Develop models and evaluation frameworks designed to scale across merchant programs, product categories, and marketplaces — enabling cross-learning and reducing the time and cost of applying science to new business contexts.

* Build and evolve optimization systems. Design and improve optimization systems — including reinforcement learning and multi-objective optimization approaches — that automate price and promotion decisions at scale across millions of products. * Apply generative AI and foundation models.

Identify and pursue opportunities to leverage large language models, embeddings, and generative AI techniques in pricing science — from enriching product representations and extracting competitive signals from unstructured data, to building more capable and explainable pricing systems. * Experiment rigorously. Design and execute A/B tests and causal inference studies to measure the business and customer impact of pricing model changes.

Translate findings into production-ready science improvements. * Stay at the frontier. Establish mechanisms to track the latest advances in reinforcement learning, causal ML, multi-objective optimization, generative AI, and demand modeling — and identify opportunities to apply them to Pricing & Promotions business problems.

* See the big picture. Contribute to the long-term scientific vision for how Amazon sets competitive, perception-preserving prices — balancing profitability, customer trust, and marketplace health. Applied Scientist, Navigation Amazon is on a mission to redefine the future of automation — and we're looking for exceptional talent to help lead the way.

We are building the next generation of advanced robotic systems that seamlessly blend cutting-edge AI, sophisticated control systems, and novel mechanical design to create adaptable, intelligent automation solutions capable of operating safely alongside humans in dynamic, real-world environments.

At Amazon, we leverage the power of machine learning, artificial intelligence, and advanced robotics to solve some of the most complex operational challenges at a scale unlike anywhere else in the world. Our fleet of robots spans hundreds of facilities globally, working in sophisticated coordination to deliver on our promise of customer excellence — and we're just getting started.

As a Sr. Scientist in Robot Navigation, you will be at the forefront of this transformation — architecting and delivering navigation systems that are intelligent, safe, and scalable.

You will bring deep expertise in learning-based planning and control, a strong understanding of foundation models and their application to embodied agents, and as well as have in-depth understanding of control-theoretic approaches such as model predictive control (MPC)-based trajectory planning. You will develop navigation solutions that seamlessly blend data-driven intelligence with principled control-theoretic guarantees.

Our vision is bold: to build navigation systems that allow robots to move fluidly and safely through dynamic environments — understanding context, anticipating change, and adapting in real time. You will lead research that bridges the gap between cutting-edge academic advances and production grade deployment, collaborating with world-class teams pushing the boundaries of robotic autonomy, manipulation, and human-robot interaction.

Join us in building the next generation of intelligent navigation systems that will define the future of autonomous robotics at scale.

Key job responsibilities - Design, develop, and deploy perception algorithms for robotics systems, including object detection, segmentation, tracking, depth estimation, and scene understanding - Lead research initiatives in computer vision, sensor fusion and 3D perception - Collaborate with cross-functional teams including robotics engineers, software engineers, and product managers to define and deliver perception capabilities - Drive end-to-end ownership of ML models — from data collection and labeling strategy to training, evaluation, and deployment - Mentor junior scientists and engineers; contribute to a culture of technical excellence - Define and track key metrics to measure perception system performance in real-world environments - Publish research findings in top-tier venues (CVPR, ICCV, ECCV, ICRA, NeurIPS, etc.) and contribute to patents A day in the life - Train ML models for deployment in simulation and real-world robots, identify and document their limitations post-deployment - Drive technical discussions within your team and with key stakeholders to develop innovative solutions to address identified limitations - Actively contribute to brainstorming sessions on adjacent topics, bringing fresh perspectives that help peers grow and succeed — and in doing so, build lasting trust across the team - Mentor team members while maintaining significant hands-on contribution to technical solutions About the team Our team is a group is a diverse group of scientists and engineers passionate about building intelligent machines.

We value curiosity, rigor, and a bias for action. We believe in learning from failure and iterating quickly toward solutions that matter. Applied Scientist II, Sponsored Products and Brands-Agent The Sponsored Products and Brands team at Amazon Ads is re-imagining the advertising landscape through 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 the team SPB Agent team's vision is to build a highly personalized and context-aware agentic advertiser guidance system that seamlessly integrates Large Language Models (LLMs) with sophisticated tooling, operating across all experiences. The SPB-Agent is the central agent that interfaces with advertisers across Ads Console, Selling Partner portals (Seller Central, KDP, Vendor Central), and internal Sales systems.

We identify high-impact opportunities spanning from strategic product guidance to granular optimization and deliver them through personalized, scalable experiences grounded in state-of-the-art agent architectures, reasoning frameworks, sophisticated tool integration, and model customization approaches including fine-tuning, MCP, and preference optimization.

This presents an exceptional opportunity to shape the future of e-commerce advertising through advanced AI technology at unprecedented scale, creating solutions that directly impact millions of advertisers.

Sr. Applied Scientist, AWS Automated Reasoning Applied Scientist, AWS Automated Reasoning Economist II, GMAC Economics Are you excited about using econometrics, experimentation, and machine learning to impact real-world business decisions? We are looking for an Economist II to work on challenging problems at the intersection of causal inference and machine learning for Prime Video Ads.

You will design experiments, build econometric and ML models, and translate findings into decisions that shape how millions of customers experience advertising on Prime Video. If you have a deeply quantitative approach to problem-solving, enjoy building and implementing models end-to-end, and want to work on problems where rigorous economics meets production-scale ML, we want to talk to you.

Key job responsibilities - Design, execute, and analyze experiments to measure the impact of ad policies on customer behavior and business outcomes - Develop causal inference models (experimental and observational) to estimate short- and long-term effects of strategic initiatives - Collaborate with scientists, engineers, and product teams to deliver measurable business impact - Influence business leaders based on empirical findings Get more from Amazon Science