Amazon has 1472 active AI-related job listings. The company is heavily focused on roles within the "agents" stage, which accounts for 38% of its AI hiring, followed by "application" at 26%. Engineering is the dominant function, with 1172 positions. Over the last 30 days, Amazon has added 667 new AI roles, representing a 74% increase compared to the previous 30-day period. Frequent tech tags include agent_orchestration, model_serving, and multimodal.
Currently tracking 1110 active AI roles, down 16% versus the prior 4 weeks. Primary focus: Agent · Engineering. Salary range $65k–$465k (avg $194k).
Amazon currently has 1573 active AI-related roles in our index. The most common open titles are: ML Data Associate-II (9), 2026 Applied Scientist Intern, Amazon University Talent Acquisition (8), AI Data Associate (Dutch) , Artificial General Intelligence Data Services (8), Software Development Engineer, AWS (8), Senior Delivery Consultant - Data , Professional Services, AWSI HCLS (7). Most positions are in Engineering and Research.
Amazon's active AI hiring is concentrated in: agents (41%), application (26%), serving infrastructure (13%). These categories follow a seven-stage AI lifecycle: data, pre-training, post-training, serving infrastructure, agents, evaluation, and application.
Amazon is hiring AI talent in: United States (1023 roles), Canada (59 roles), United Kingdom (47 roles), India (23 roles).
Job postings at Amazon most frequently mention: Machine Learning, Generative AI, Large Language Models (LLMs), Software Engineering, Agentic Systems.
In the past 30 days, Amazon has posted 696 new AI-related roles.
| Title | Stage | AI score |
|---|---|---|
| Senior Data Scientist, MAPLE - Recommender System Develops and deploys data-driven models for shopping personalization and recommendation systems, leveraging GenAI techniques and causal machine learning. Focuses on improving customer experience through supervised and uplift learning, A/B testing, and harnessing large-scale data. The role involves publishing research and mentoring junior scientists. | Ship | 7 |
| Applied Scientist, Core Search This role focuses on building and improving ML-powered search ranking models at Amazon's scale, leveraging large datasets and exploring techniques like reinforcement learning to enhance customer experience. The primary deliverable is the shipped AI product (search ranking system). | Ship |
| 7 |
| Applied Scientist, Amazon Ads, Demand Forecasting & Guidance The Applied Scientist will lead Machine Learning efforts for Amazon Ads' Demand Forecasting & Guidance team. This role involves hands-on analysis and modeling of large datasets to develop insights, build and deploy ML models into production, and run A/B experiments. The goal is to create best-in-class forecasting products for advertisers to predict campaign outcomes and optimize ad performance, directly impacting key business decisions. | Ship | 7 |
| Data Scientist, IES CFX & Prime This role focuses on developing and deploying machine learning systems to protect Amazon's online marketplace from fraudulent customer behavior and improve customer experience. It involves using GenAI for promotions and collaborating with cross-functional teams to build scalable ML solutions. | Ship | 7 |
| Software Development Engineer, Ring Cloud Computer Vision Software Development Engineer role focused on building and scaling AI-powered computer vision cloud services for Ring's consumer electronics products, serving tens of millions of users globally. The role involves full software development lifecycle, from design and development to deployment and operations, with a focus on high-availability, resilience, and scalability. | Ship | 7 |
| Applied Scientist II, Amazon Stores Economics and Science (SEAS) Applied Scientist role focused on building and delivering state-of-the-art science and engineering solutions for Amazon's Stores business, leveraging machine learning, optimization, and economics to improve business metrics. The role involves developing and maintaining scientific models, benchmarks, and services, and deploying solutions in partnership with product teams. | Ship | 7 |
| Applied Scientist II, Buyer Risk Prevention (BRP) Applied Scientist II role focused on building and deploying end-to-end machine learning models for fraud and risk prevention in an e-commerce environment. The role involves leveraging Generative AI and LLMs to enhance detection systems, analyzing large datasets, and collaborating with engineering and business stakeholders. Requires experience in model development from problem formulation to production, with a focus on scalable ML solutions. | Ship | 7 |
| Applied Scientist, AWS Applied AI Solutions Core Services Applied Scientist role focused on developing and productizing AI solutions for enterprise services within AWS. The role involves designing and implementing ML systems for diverse applications, creating scalable algorithms, conducting experimentation with advanced techniques (LLMs, CV, agentic AI), and collaborating with engineering and product teams to deliver customer impact. The primary output is shipped AI products, with a secondary focus on agentic AI systems. | ShipAgent | 7 |
| Software Development Engineer, RecsAI - Personalization Software Development Engineer role focused on building and scaling Amazon's next-generation recommendation system (RecsAI) which uses LLMs trained for shopping to provide personalized product suggestions. The role involves designing, building, testing, and operating features for this system, collaborating with product and science teams, and ensuring maintainability, scalability, performance, and reliability at Amazon scale. It emphasizes end-to-end ownership, experimentation, and integrating generative AI into real-time recommendation experiences. | Ship | 7 |
| Data Scientist II (ADBL175) Data Scientist II at Audible (Amazon) focused on building production-ready LLM solutions and recommendation systems. Requires a Master's degree and 2+ years of experience in data science, ML modeling, Python/R, and non-linear models. Experience with LLMs (programmatic access, evaluation, fine-tuning), recommendation systems, and SQL/ETL is required. | ShipPost-train | 7 |
| Software Development Engineer II, Featured Merchant Algorithm Software Development Engineer II on the Featured Merchant Algorithm team at Amazon. This role involves working with machine learning models to select the best offer for customers on Amazon's product detail pages and search results. The team focuses on optimizing customer experience by considering factors like price, availability, and delivery options. The engineer will collaborate with various stakeholders to strategize and launch new features, using data to drive decisions and present impact. | Ship | 7 |
| Applied Scientist II, Amazon Fulfillment Technology (AFT) Science Applied Scientist II at Amazon Fulfillment Technology (AFT) Science, focusing on developing production solutions for Amazon's Fulfillment Network using operations research, optimization, statistics, machine learning, and GenAI/LLM. The role involves designing, building, and deploying scalable mathematical models and optimization-driven solutions to improve process efficiency and associate experience within the fulfillment network. Collaboration with scientists, software engineers, and product managers is key, with a focus on translating research into production systems. | Ship | 7 |
| Senior Manager, Applied Science, Network Planning Solutions Senior Manager role focused on leading AI/ML innovation for network planning solutions, involving demand forecasting and network optimization algorithms. The role requires developing and deploying production-ready models, architecting scalable AI/ML infrastructure, and driving scientific innovation from research to production, ultimately translating AI/ML capabilities into measurable business outcomes. It emphasizes leading a team of applied scientists and collaborating with cross-functional partners. | ShipData | 7 |
| Data Scientist, SPX AI Lab, SPX Science The role focuses on applying advanced analytical, statistical, and machine learning techniques to improve Amazon's Selling Partner experience through a Generative AI-powered conversational assistant. Responsibilities include analyzing seller pain points, evaluating feature performance, designing measurement frameworks (A/B testing, causal inference), applying NLP and statistical modeling to unstructured data, and partnering with cross-functional teams to influence product roadmaps. The goal is to enhance the Selling Assistant by responding to seller feedback and implementing fixes in the GenAI solution. | Ship | 7 |
| Applied Scientist, Amazon Ads, Demand Forecasting & Guidance Applied Scientist role at Amazon Ads focusing on Generative AI, AI Agents, and large-scale ML for demand forecasting. Responsibilities include leading ML initiatives, developing and optimizing forecasting models, building and deploying ML models, designing A/B experiments, establishing scalable ML infrastructure, and researching innovative ML techniques. Requires 3+ years of model building experience, a PhD or Master's with 4+ years of experience in a related field, and programming experience in Java, C++, or Python. Preferred qualifications include experience with experimental design and deep learning frameworks. | ShipServe | 7 |
| Software Development Engineer 2, Amazon Business Software Development Engineer 2 role on the Unified Risk Evaluation System team at Amazon Business, focusing on fraud prevention and risk management using machine learning and scalable systems to process billions of transactions globally. The team builds self-service capabilities for ML model experimentation and manages numerous risk use cases. | Ship | 7 |
| Sr Applied Scientist, Amazon Shipping Lead ML teams building large-scale forecasting and optimization systems for Amazon's global transportation network, impacting customer experience and cost. The role involves setting scientific direction, mentoring scientists, and delivering production-grade ML solutions at scale, using techniques like deep learning and reinforcement learning. | Ship | 7 |
| Senior Applied Scientist, Amazon Industrial Robotics Senior Applied Scientist role focused on developing next-generation advanced robotics systems that combine AI, control systems, and mechanical design for automation at Amazon's scale. The role involves research and implementation of deep learning and LLMs for robotics, with a focus on simulation, physics-based modeling, and sim-to-real gap reduction. | Ship | 7 |
| Sr. Manager, Applied Science, Marketing Measurement and Performance Science (MAPS) Senior Manager, Applied Science for Marketing Measurement and Performance Science (MAPS) at Amazon. This role focuses on building scalable ML and causal inference solutions to estimate marketing effectiveness and provide insights for marketing teams. It involves leading a team of scientists, developing end-to-end causal inference models, and influencing multi-billion dollar investment decisions. The role requires expertise in ML/DL, statistics, economics, and handling large datasets at scale, with a focus on delivering data-driven solutions that impact business strategy and customer behavior. | Ship | 7 |
| Applied Scientist, Private Brands Discovery Applied Scientist role focused on designing and building machine learning solutions for customer discovery of Amazon's Private Brands. The role involves end-to-end project management from ideation to launch, with a strong emphasis on causal ML, deep learning, and deploying models to production. The goal is to drive customer awareness and product discovery, impacting Amazon's own brands and contributing to broader discovery solutions across the company. | Ship | 7 |
| Senior Applied Scientist, Amazon Stores Economics & Science (SEAS) Senior Applied Scientist role focused on applying optimization, statistical learning, and algorithm development to solve complex supply chain and marketplace problems within Amazon's Stores organization. The role involves leading science initiatives from research to production, designing algorithms for mechanism design, and influencing technical strategy. | Ship | 7 |
| Sr. Applied Scientist, Last Mile Science The Sr. Applied Scientist role in Amazon Logistics focuses on optimizing last-mile delivery operations through the development and application of machine learning models and algorithms. The role involves estimating costs, improving metrics, developing scalable processes, and working with technology teams to build new tools and systems that impact customer experience and delivery efficiency. It requires a PhD or equivalent experience in a quantitative field and strong analytical and program management skills. | Ship | 7 |
| 2026 Applied Scientist Intern, Amazon University Talent Acquisition MS or PhD student internship in machine learning, deep learning, generative AI, LLMs, speech technology, robotics, computer vision, optimization, operations research, quantum computing, automated reasoning, or formal methods. Focus on designing and implementing state-of-the-art solutions for complex problems, potentially leading to production deployment and publication. | Ship | 7 |
| 2026 Data Scientist Internship , Amazon University Talent Acquisition MS student internship focused on building and deploying machine learning models for Amazon's business problems, with potential for worldwide scale. The role involves working with large datasets and cloud technology, and defining metrics for customer satisfaction. | Ship | 7 |
| Sr. Manager, Applied Science, Sponsored Products and Brands This role leads science and engineering for AI-powered sponsored product ads in offsite shopping experiences, focusing on generative AI and large-scale ML solutions. The goal is to revolutionize advertising by bridging human creativity with AI, impacting ad creation, optimization, performance analysis, and customer insights. The role involves extending campaigns to reach customers off-store and on third-party sites, working with external and internal partners, and driving results at scale with a GenAI-first approach. It requires significant experience in building large-scale ML/AI solutions and people management. | Ship | 7 |
| Principal Applied Scientist, Personalization Principal Applied Scientist role focused on building next-generation personalized shopping experiences at Amazon using LLMs, transformer models, and large-scale ranking systems. The role involves innovating features and models, leading science innovation, driving the science roadmap, and mentoring scientists. It aims to create a personalized shopping experience tailored to customer intent and product catalog understanding. | ShipAgent | 7 |
| Sr. Applied Scientist, Prime Video - Personalization and Discovery Science This role focuses on developing and launching end-to-end AI solutions for Prime Video's search and discovery systems, utilizing deep learning, GenAI, and reinforcement learning. The scientist will design and conduct experiments, collaborate with engineers and product managers, and publish research findings. The role is within the consumer domain, aiming to improve customer experience for millions of users. | Ship | 7 |