Senior Applied Scientist role focused on building Generative AI models for conversational ads and personalization within the Alexa ecosystem. The role involves designing, developing, and evaluating deep learning and GenAI models, conducting data analysis, building ML pipelines, running A/B experiments, and collaborating with engineers for production deployment. The team is greenfield, aiming for direct business impact and encouraging both production deployment and top-tier publications.

Applied Scientist II at Amazon Alexa Ads focused on building Generative AI models for conversational ads and personalization. The role involves designing, developing, and evaluating deep learning and GenAI models, conducting data analysis, building ML pipelines, running A/B experiments, and collaborating with engineers for production deployment. The team is greenfield, aiming to rethink ad ranking, pricing, and personalization for voice and screen surfaces, with opportunities for both shipping products and publishing research.

Senior Manager, Applied Science at Amazon Prime Video Advertising, leading a team to build and scale ML/AI solutions for advertising optimization, experimentation, and generative AI-powered ad creative generation. The role involves setting scientific vision, managing managers, and driving strategic initiatives in a rapidly growing business.

This role focuses on designing and implementing generative AI solutions for government customers using AWS services. The Solutions Architect will act as a Subject Matter Expert, guiding customers and internal teams on leveraging AI for automation and cost reduction. The role requires deep technical experience in AI/ML and integrating these services into production applications.

This role focuses on designing and implementing generative AI solutions for government customers using AWS services. The Solutions Architect will act as a Subject Matter Expert, guiding customers and internal teams on leveraging AI for automation and cost reduction. The role requires deep technical experience in AI/ML and integrating these services into production applications.

Amazon is seeking Applied Scientists to build software and machine learning models for customer discovery experiences, focusing on ranking, recommendations, and computer vision. The role involves developing and deploying state-of-the-art models, including text-to-image and image-to-text, to enhance customer engagement with the Amazon catalog.

The Principal Applied Scientist will lead the development and deployment of generative AI technologies for Amazon Ads, specifically within the Sponsored Products and Brands team. This role involves reinventing advertising experiences by integrating AI into the ad lifecycle, from creation to performance analysis. The scientist will invent new product experiences, bring state-of-the-art GenAI models to production, and define the long-term science vision for the advertising business, collaborating closely with science, product, and engineering teams to deliver high-impact products.

Principal Applied Scientist for Amazon Payments AI/ML Team, focusing on AI services for payments, recommendation, prediction, and GenAI for SOP automation. The role involves setting AI direction, mentoring scientists, partnering with engineering to deliver ML/GenAI features, identifying research directions, creating roadmaps, and bringing research to production. Requires a PhD or MSc with 10+ years of experience, a track record of thought leadership, and strong collaboration skills.

Senior Manager of Applied Science at Amazon, leading a multidisciplinary team to build the next generation of personalized shopping experiences. The role involves developing state-of-the-art LLM-based techniques, deep learned transformer models for customer intent, and large-scale real-time multi-task ranking systems. The goal is to create AI primitive systems that empower other teams and directly impact millions of customers through personalized features.

Internship role focused on applying state-of-the-art Deep Learning, Recommender Systems, Information Retrieval, and NLP algorithms to large datasets for customer-facing products at Amazon. Involves developing novel solutions, building prototypes, contributing to research, and potentially delivering solutions to production. Collaboration with experienced scientists and opportunities for publication in top conferences.

This role focuses on developing and applying ML models, including foundation models, for recommendation and search systems within Prime Video's personalization and discovery science team. The goal is to enhance customer experience by recommending titles effectively and enabling discovery of niche interests. The role involves end-to-end ownership, experimentation, and collaboration with scientists, engineers, and product managers, with an emphasis on publishing research findings.

Sr. Applied Scientist at Amazon Prime Video focused on developing and launching AI solutions for personalization and discovery systems, impacting millions of customers.

This role focuses on developing and applying ML models, including foundation models, for recommendation and search systems within Prime Video's personalization and discovery science team. The goal is to enhance customer experience by recommending titles effectively and enabling discovery of niche interests. The role involves end-to-end ownership, experimentation, and collaboration with scientists, engineers, and product managers, with an emphasis on publishing research findings.

Director of Science, Geospatial at Amazon, leading a team of ~50 scientists focused on AI/ML solutions for last-mile delivery operations. The role involves developing and deploying solutions for geospatial problems, including address validation, place datasets, road networks, and leveraging edge data. Key focus areas include GenAI (LLMs, VLMs, agents), computer vision, and traditional ML to optimize delivery routes, improve data fidelity, and drive business impact. The role requires interfacing with senior stakeholders, strategic planning, and building a high-performing team.

Senior Applied Scientist role focused on developing and deploying AI/ML models and analytics for customer-facing AI solutions within Amazon Connect. The role involves working directly with customers to accelerate production deployments, designing and building AI solutions, conducting experiments, quantifying business value, and applying NLP/generative AI techniques. It spans conversational analytics and agentic AI capabilities, with a strong emphasis on driving measurable business impact and operational excellence in customer environments.

This role focuses on applying Generative AI and LLMs to transform ad experiences on Amazon's homepage and other surfaces, impacting product discovery and customer engagement. It involves building and deploying models for ad retrieval, auctions, and personalized shopping experiences, operating across the full stack from backend systems to the user-facing layer.

Applied Scientist II role focused on developing advanced robotics systems using AI, deep learning, and reinforcement learning for automation at Amazon's scale. The role involves designing and implementing control methods for balance, locomotion, and manipulation, with a focus on bridging theoretical advancements and practical implementation in robotics.

Manager for an AWS Generative AI Innovation Center focused on building and delivering generative AI solutions for customers, managing a team of scientists and engineers, and driving adoption and strategic relationships.

This role focuses on developing advanced robotics systems that integrate AI, control systems, and mechanical design for automation. The scientist will define the scientific roadmap for whole body control and dexterous manipulation, applying deep learning and LLMs to solve complex operational challenges in dynamic environments. The role involves research and practical implementation of AI in physical robotic hardware, with a focus on shipping these systems.

Senior Manager to lead an AI-first security technology organization, owning the enterprise AI/ML roadmap, leading a team of scientists and BIEs, and delivering production AI/ML models for efficiency gains and loss reduction. The role involves establishing AI/ML delivery standards, building MLOps infrastructure, and partnering with business and technical leaders, while ensuring responsible AI and compliance with regulations.

This role is for a Sr. Applied Scientist on an Amazon Special Projects team focused on creating new products and services. The role involves leading research projects from ideation to production, driving ML/AI strategy, collaborating cross-functionally, publishing findings, and establishing best practices for ML experimentation and deployment. Requires a PhD or Master's with significant applied research experience, strong programming skills, and experience with ML/LLM fundamentals and deploying ML systems at scale. Experience with autonomous AI frameworks and translating research into production systems is preferred.

Applied Scientist role focused on building and deploying AI/ML models for customer behavior prediction and personalization within Amazon Prime. The role involves working with large-scale data, leveraging GenAI, LLMs, deep learning, and reinforcement learning, and contributing to production AI/ML systems. Emphasis on scientific research, publication, and utilizing AWS technologies.

Applied Scientist focused on developing learning-based approaches for mobile manipulation in robotics, aiming to advance capabilities for robots navigating and manipulating objects in dynamic fulfillment environments. The role involves model development, training, data management, experimentation, validation, and code development for production systems at Amazon's scale.

This internship focuses on developing and implementing cutting-edge computer vision algorithms and models for Amazon's consumer-facing products and services, such as Rekognition, Go, and Visual Search. The role involves working with large-scale systems, including mobile robots and advanced tooling, to solve real-world problems. Interns will contribute to production-level projects, technical white papers, and roadmaps, with a strong emphasis on applied science and deep learning in computer vision, potentially involving Vision-Language Models and LLMs.

This internship focuses on developing and evaluating new recommendation and search algorithms, building data processing pipelines, and conducting research in recommender systems and information retrieval. The role involves applying machine learning, deep learning, and NLP techniques to large-scale datasets to improve personalized experiences for Amazon customers.

Senior Applied Scientist role at AWS Healthcare AI, focusing on developing and researching AI-driven clinical solutions to transform healthcare delivery. The role involves defining research directions, developing new ML techniques, and ensuring research translates into impactful products for clinicians and patients. Requires a PhD or Master's with significant experience in ML, NLU, deep learning, foundation models, and RL, with a strong publication record.

Principal Applied Scientist role at Prime Video focused on inventing, developing, and deploying AI solutions for personalization and discovery. The role involves technical and strategic leadership, guiding ML systems from research to production, and mentoring scientists. Key responsibilities include prototyping and productionizing large-scale AI solutions using deep learning, generative AI, RL, and optimization, providing technical leadership, designing A/B tests, driving technical bar-raising, and staying ahead of industry trends. The team focuses on creating a highly personalized content discovery experience using ML and Generative AI.

This role focuses on developing and launching end-to-end AI solutions for Prime Video's recommendation and personalization systems. It involves deep learning, GenAI, reinforcement learning, and optimization methods, with a strong emphasis on experimental design (A/B testing) and research publication. The scientist will work closely with engineers and product managers to bring these solutions to millions of customers.

Research scientist role focused on developing novel machine learning solutions for music and podcast recommendations within Amazon Music. The role involves implementing and validating ideas through A/B testing, producing innovative research for peer-reviewed publications, and building scalable models. It requires a PhD or Master's degree and experience in deep learning, ML, or NLP, with a focus on recommender systems.

Manager for a team of applied scientists and ML engineers focused on building generative AI solutions for advertisers within Amazon Advertising. The role involves setting scientific strategy, mentoring scientists, managing talent, and delivering AI products at scale, with a focus on multi-modal generative AI for creative assets.

This role leads teams of applied scientists and ML engineers to develop and deliver AI systems for Amazon businesses, focusing on integrating information into AI systems using techniques like RAG. The role involves defining technical roadmaps, mentoring teams, and driving research from conception to production, with a strong emphasis on building impactful AI-driven products and services.

Senior Applied Scientist role focused on developing AI and ML systems for industrial robotics and manufacturing, involving real-time decision making, optimization, and inventing new algorithms. The role requires delivering complex solutions into production and has a strong emphasis on scientific code development and evaluation.

Senior Applied Scientist role focused on research, design, and development of new AI technologies for personalization, including recommendation systems and large language models. The role involves inventing, experimenting with, and launching new features, products, and systems that impact millions of customers.

Research Scientist role focused on developing and launching new AI technologies for personalization, leveraging large datasets and computational resources to build large-scale machine learning solutions for customer recommendations. The role involves inventing, experimenting with, and launching new features, products, and systems, with a strong emphasis on research publications.

Applied Scientist role focused on designing, developing, and deploying machine learning and computer vision models for Amazon's in-store grocery technologies. The role involves end-to-end model development, from ideation to production, with a focus on solving complex grocery-domain problems at scale and improving the customer shopping experience.

Senior Deep Learning Architect focused on implementing and fine-tuning Generative AI solutions for AWS customers, involving customer interaction, solution design, experimentation, and providing guidance on adoption and best practices. The role bridges customer needs with technical implementation and feedback to product teams.

Manager for an Applied Science team focused on Brand Protection ML at Amazon. The role involves leading scientists to build and launch scalable AI/ML/LLM/GenAI solutions to identify and prevent infringement and counterfeit on Amazon's platform globally. The team works on complex business problems with significant customer impact, leveraging SOTA ML techniques and deep learning, computer vision, and NLP.

Applied Scientist role focused on building and deploying Generative AI solutions for Brand Protection using NLP, computer vision, and LLMs. The role involves end-to-end ownership from conception to launch, collaborating with product and engineering teams, and analyzing data to solve complex business problems at scale.

This role focuses on developing AI and ML solutions for last mile delivery automation, combining expertise in machine learning, computer vision, and robotics to solve complex challenges in perception, navigation, and path planning. The scientist will research, design, and implement algorithms, transforming research concepts into production-ready solutions for autonomous systems.

Applied Scientist role focused on building Generative AI models for conversational ads and personalization within the Alexa ecosystem. Responsibilities include designing, developing, and evaluating ML models for NLP, recommendation systems, and personalization, conducting data analysis, building ML pipelines, running A/B experiments, and collaborating on production deployment.

Senior Applied Scientist role at Amazon focusing on Generative AI for Alexa Conversational Ads and Personalization. Responsibilities include defining scientific vision, leading ML projects, architecting large-scale ML systems, mentoring junior scientists, and collaborating with product/engineering. Requires experience in building ML models for business applications, ML/LLM fundamentals, and large-scale systems. Preferred experience in ad tech and building ML models for recommendations, ads ranking, personalization, or search.

Applied Scientist role focused on leveraging computer vision, generative AI, and deep learning to enhance vehicle navigation and ensure safe, efficient deliveries by analyzing multimodal data. The role involves building large-scale ML systems, translating business requirements into prototypes, and optimizing models for production and edge devices.

Senior Applied Scientist role focused on building state-of-the-art ML models for healthcare challenges within Amazon's Special Projects team. The role emphasizes practical implementation, driving ML advancements, and delivering products to market in an entrepreneurial, startup-like environment. Requires a strong background in AI/ML, leadership skills, and the ability to translate research into actionable plans and practical solutions.

MS or PhD student internship focused on machine learning, deep learning, generative AI, LLMs, speech, robotics, computer vision, optimization, operations research, quantum computing, automated reasoning, or formal methods. The role involves designing and developing end-to-end systems, writing technical white papers, creating roadmaps, and driving production-level projects. Interns will work closely with scientists to develop and deploy solutions, design new algorithms and models, and potentially publish work at top-tier conferences.

Applied Scientist II role focused on building AI-based services for Amazon Q Developer, aiming to redefine developer workflows. The role involves working on ambiguous problem areas, driving the delivery of end-to-end modeling solutions, and collaborating with other AWS AI services. The team builds AI products deployed in IDEs, AWS console, and web tools, providing developers with AI assistants for code generation and AWS interaction.

Principal Data Scientist role at Amazon ProServe, focusing on architecting and implementing enterprise-scale AI/ML and generative AI solutions for customers. Requires technical leadership, strategic advisory, and developing reusable frameworks. Involves customer-facing engagements and mentoring junior data scientists. Requires Top Secret clearance.

Principal Data Scientist role at Amazon ProServe, focusing on architecting and implementing enterprise-scale AI/ML and generative AI solutions for AWS customers. Requires technical leadership, strategic advisory, and driving customer adoption of AWS AI/ML services. Involves leading complex initiatives, translating business challenges into technical solutions, and developing reusable frameworks. Requires a Top Secret security clearance.

Senior Applied Scientist at AWS Healthcare AI focused on developing and researching AI-driven clinical solutions to transform patient-clinician interaction and care documentation. The role involves leading research, developing new ML techniques, and ensuring research translates into impactful products, with a focus on generative AI experiences.