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.

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.

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.

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.

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.

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.

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.

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.

PhD intern/co-op role in Amazon's Personal Robotics Group focusing on research and development of intelligent robotic products, including Amazon Astro. The role involves working on the full spectrum of robotics, from hardware design to software and control systems, with a focus on manipulation, locomotion, and human-robot interaction. Requires a PhD in a relevant field and experience in programming languages like Python, C++, or Java.

This role focuses on developing next-generation advanced robotics systems by combining AI, control systems, and mechanical design for automation at Amazon's scale. The intern will contribute to research bridging theoretical advancements and practical implementation in robotics, focusing on areas like dexterous manipulation, locomotion, and human-robot interaction, leveraging deep learning and LLMs.

This role focuses on applying advanced automated reasoning techniques, including SAT, SMT, symbolic simulation, and program analysis, to solve complex problems within AWS. The goal is to enhance privacy and sovereignty for AWS services, impacting business and customer outcomes through scientific innovation and strategic problem-solving.

Applied Scientist role at Amazon Ads focusing on generative AI for sponsored products and brands. The role involves developing and researching real-time ML algorithms for ad auctions and multi-objective optimization, aiming to improve customer experience and drive revenue. It requires end-to-end ML project ownership in a highly ambiguous and large-scale environment.

Applied Scientist role at Amazon Prime Video focusing on personalization and discovery science. The role involves developing AI solutions for search systems using deep learning, GenAI, and reinforcement learning, with end-to-end ownership from design to launch. It requires designing and conducting experiments, and publishing research findings. The team owns science solutions for search experience, including sourcing, relevance, and ranking.

This role focuses on developing advanced robotics systems that integrate AI, control systems, and mechanical design for automation. The scientist will design and implement whole-body control methods for balance, locomotion, and dexterous manipulation, utilizing state-of-the-art learned and model-based control methods, including imitation learning and reinforcement learning. The goal is to create robust, safe, real-time controllers for robots operating in dynamic environments and alongside humans.

Applied Scientist II at Amazon Prime Video focused on developing ML models for recommendation and search systems using deep learning, online learning, and optimization methods. The role involves end-to-end ownership of product and user experience, working with advanced approaches like foundation models to tackle cold-start problems and discover niche interests. The scientist will also publish research findings and collaborate with engineering and product teams.

Applied Scientist role at Amazon Prime Video focusing on leveraging NLP and Computer Vision research to enhance video content understanding and customer experience. The role involves leading research direction, creating roadmaps, and developing models for business applications, with an emphasis on delivering state-of-the-art digital video experiences.

Research scientist role focused on developing and launching new AI technologies for personalization in e-commerce, leveraging LLMs, recommendation systems, and information retrieval.

Applied Scientist role focused on developing and launching AI solutions for Prime Video's personalization and discovery systems, involving deep learning, GenAI, RL, and optimization. The role requires end-to-end ownership, experimental design (offline and A/B testing), and publishing research findings. Experience with recommender systems and personalization is preferred.

Applied Scientist role focused on developing and launching customer-obsessed pricing algorithms for billions of products worldwide. This involves leveraging large-scale multi-modal datasets, applying machine learning, predictive modeling, causal inference, and reinforcement learning to optimize pricing strategies and tools for sellers. The role emphasizes collaboration with product and engineering teams, continuous learning, and delivering business impact through innovative pricing solutions.

Applied Scientist role focused on developing and deploying machine learning models to optimize marketing initiatives and predict customer behavior for Amazon's consumer business. Requires strong quantitative modeling, statistical methods, and experience with deep learning.

Research Scientist II Intern/Co-op role in Amazon's Personal Robotics Group, focusing on developing intelligent robotic products and systems. The role involves research in areas like robotics manipulation, autonomous navigation, locomotion, controls, perception, robot learning, AI, ML, computer vision, LLMs, and HRI, with a goal of impacting millions of customers. The position is for PhD students and involves working on scalable research projects.

The role involves applying deep learning, neural networks, and transformer architectures to price prediction and forecasting problems within Amazon's Pricing Optimization group. It focuses on developing and deploying ML models at scale to improve pricing and promotion strategies, requiring collaboration with product, engineering, and science teams.

The Economist II, Featured Merchant Algorithm role at Amazon focuses on developing and deploying machine learning models that determine the 'Buy Box' offer and surrounding customer experience on Amazon's platforms. This involves ranking and selecting the best offer based on factors like price, availability, and delivery, impacting billions of transactions daily. The role requires a PhD in economics, strong data-driven decision-making, collaboration with cross-functional teams, and expertise in prediction and forecasting with large datasets.

This internship role focuses on applying data science and machine learning to solve complex problems in robotics at Amazon. Interns will design and implement solutions, research new algorithms, collaborate with experts, and build tools to improve robotics analytics and customer experience. The role involves working with various AI/ML fields including computer vision, LLMs, and deep learning within a robotics context.

Applied Scientist II at Amazon Prime Video focusing on personalization and discovery science. The role involves developing ML models for recommendation and search systems using deep learning, online learning, and optimization methods. It requires staying updated with the latest modeling techniques, publishing research findings, and applying advanced approaches like foundation models to solve cold-start problems and discover niche customer interests. The scientist will work on highly scalable page personalization solutions and collaborate with engineers and product managers.