Senior Applied Scientist at Amazon Ads focusing on applying cutting-edge generative AI and LLMs to the advertising life cycle. The role involves researching, developing, and deploying ML solutions for ranking, personalization, NLP, computer vision, recommender systems, and LLMs. It requires driving end-to-end projects, building and optimizing models, running A/B experiments, and developing scalable ML processes. The role emphasizes impacting millions of customers and advertisers through innovative ML solutions at massive scale.

Senior Manager of Applied Science for Alexa Connections, leading a team to build LLM-powered communication features for millions of users. Focuses on end-to-end applied science projects, from ideation to deployment and monitoring, with an emphasis on scaling ML models and AGI/LLM systems for consumer applications.

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.

Principal Applied Scientist role focused on developing and deploying generative AI solutions for Amazon's Sponsored Products and Brands advertising platform. The role involves defining science vision, building ML/LLM models for advertiser and shopper experiences, optimizing campaign performance, and leading scientific rigor. Requires strong ML, LLM, and GenAI expertise with experience in production systems and digital advertising.

Manager for an Applied Science team focused on innovating AI features for Ring and Blink cameras, combining computer vision and generative AI for home security. The role involves leading the team in developing and productizing advanced CV and GenAI models, driving technical strategy for privacy-preserving solutions, and ensuring delivery of high-quality science artifacts for customer-facing products.

Senior Manager role leading a team of Applied Scientists and Engineers to develop and deploy generative AI solutions for Amazon's Sponsored Products and Brands advertising platform, focusing on multi-lingual and multi-modal applications to drive growth in non-US markets.

The RBKS AI team at Amazon is seeking Applied Scientists to innovate AI features for Ring and Blink cameras, focusing on the intersection of computer vision, generative AI, and ambient intelligence. The role involves productizing research into advanced computer vision and multimodal GenAI models for video understanding, object detection, and real-time applications, with an emphasis on privacy-preserving, efficient fine-tuning, and on-device/in-cloud inference. The goal is to ship AI solutions that enhance home security for millions of customers.

Applied Scientist II role focused on developing and deploying sophisticated AI solutions for Amazon's Strategic Account Services (SAS) organization, leveraging deep learning, LLMs, and advanced ML techniques to improve seller operations and internal consultancy. The role involves end-to-end development from research to production, including architecting recommendation and optimization systems, pioneering applications of foundation models, and conducting rigorous A/B experiments.

Data Scientist II role focused on applying statistical, machine learning, or GenAI methodologies to enhance employee experience within Amazon's People Experience and Technology organization. The role involves designing, developing, and maintaining scalable models and prototypes, partnering with cross-functional teams, and communicating results to diverse audiences.

Applied Scientist role focused on developing and deploying optimization, simulation, and machine learning solutions for Amazon's Fulfillment Network. The role involves understanding operational processes, developing mathematical models, creating prototypes, partnering with engineers for production integration, and designing experiments to test solutions. The team has expertise in operations research, optimization, scheduling, planning, simulation, and machine learning.

Software Development Engineer role focused on building AI systems for Amazon's Shopping Personalization. The role involves designing and implementing features that use generative AI and LLMs to personalize product discovery and recommendations for customers at Amazon scale. Emphasis on end-to-end ownership, scalability, reliability, and collaboration with product and science teams.

Delivery Consultant for AWS Professional Services focused on AI/ML and GenAI solutions in the Healthcare and Life Sciences sector. Responsibilities include end-to-end project implementation, designing ML pipelines and MLOps, collaborating with cross-functional teams, and advising customers on AI/ML strategies using AWS services.

This role is for a Delivery Consultant on the AWS Professional Services team, focusing on designing, implementing, and managing AI/ML and Generative AI solutions for enterprise customers. The consultant will work with customers to understand business needs, prepare data, develop and deploy models, and ensure solutions are scalable, secure, and performant using AWS services and MLOps best practices. The role involves acting as a trusted advisor, collaborating with cross-functional teams, and sharing knowledge.

ML Engineer role focused on building and deploying AI/ML products for Amazon Tablets, specifically enhancing customer engagement through personalized recommendations and content ranking. The role involves end-to-end ML pipeline development, MLOps, and leveraging deep learning, LLMs, and generative AI for on-device experiences. It emphasizes shipping customer-facing ML solutions at Amazon scale.

Machine Learning Engineer II at Amazon, focusing on Search Engine Technologies and Document Retrieval within the consumer domain. The role involves applying ML models to improve customer experiences in the online retail search application, processing large datasets, and integrating models into production systems at scale.

Machine Learning Engineer II at Amazon, focusing on Search Engine Technologies and Document Retrieval within the consumer domain. The role involves applying ML models to improve customer experiences in the online retail search application, processing large datasets, and integrating models into production systems at scale.

Manager for an Applied Science team focused on extending Amazon Ads campaigns beyond the Amazon store using generative AI and machine learning to deliver sponsored experiences in third-party environments. The role involves leading scientists and engineers, shaping product direction, developing roadmaps, and driving advertiser outcomes through ML/GenAI solutions.

This role focuses on building and deploying machine learning models for Amazon Devices Sales and Marketing, specifically for product recommendations, customer segmentation, and marketing initiative effectiveness. The candidate will own solutions end-to-end, from conceptualization to productionalization, and will collaborate with various teams to deliver customer-facing reporting tools and automated recommendation systems.

This role focuses on developing and deploying AI/ML products and research models to optimize operations within Amazon's Rest of the World (ROW) region. Responsibilities include analyzing data, developing models using Python/R, creating science-based supply chain solutions, and implementing ML solutions for abuse detection. The role involves working with various teams to deliver high-quality data and science products.

Research Scientist role focused on applying Operations Research, forecasting, machine learning, and decision optimization to solve large-scale problems in Amazon's Global Real Estate and Facilities (GREF) organization. The role involves translating business problems into mathematical solutions, building scalable algorithms, and influencing operational decisions to optimize areas like employee routes, demand forecasting, capacity planning, resource allocation, cost reduction, and service reliability.

Research Scientist role focused on applying Operations Research, forecasting, machine learning, and decision optimization to solve large-scale problems in Amazon's Global Real Estate and Facilities (GREF) organization. The role involves translating business problems into mathematical solutions, building scalable algorithms, and influencing operational decisions to optimize areas like employee routes, demand forecasting, capacity planning, resource allocation, cost reduction, and service reliability.

This role focuses on applying machine learning and GenAI to develop forecasting and optimization models for Amazon's physical retail presence, supporting real estate and network planning decisions. The scientist will design, implement, and own end-to-end ML solutions, including MLOps, and enhance user interaction with GenAI. The role involves analyzing large datasets, presenting findings to leadership, and collaborating with cross-functional teams.

Applied Scientist role focused on developing and optimizing Visual Inertial Odometry (VIO) and sensor fusion systems for intelligent robots, involving algorithm development, embedded deployment, and leveraging ML for perception. The role requires hands-on experience with sensors, hardware, and real-world data, with a focus on real-time performance on resource-constrained robotic platforms.

Software Development Manager for GenAI Evaluation Media (GEM) team at Amazon, focusing on visual shopping experiences. The role involves leading a team to drive technical vision and execution of AI capabilities for generating and governing billions of visual assets at scale, ensuring quality and trustworthiness for customer purchase decisions. Requires strong technical expertise, business acumen, and leadership skills to partner with stakeholders, drive innovation, and maintain operational excellence.

Senior Technical Product Manager for advanced robotics systems, focusing on AI, control systems, and mechanical design for automation at scale. Requires deep robotics engineering expertise, including motion planning, control systems, computer vision, and machine learning, with experience in ROS, real-time OS, and embedded systems. Role involves translating technical requirements into roadmaps, evaluating tradeoffs, and driving product strategy for robotic manipulation, locomotion, and human-robot interaction.

Software Development Engineer role focused on building solutions for Sponsored Products and Brands, utilizing generative AI, machine learning, and high-scale low-latency systems to improve customer experiences off the Amazon store. The role involves designing and developing components, big data systems, and ML-based approaches in collaboration with scientists and economists.

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.

This role focuses on implementing end-to-end AI/ML and GenAI solutions for enterprise customers using AWS services. The consultant will design, deploy, and manage these solutions, focusing on MLOps and customer success throughout the project lifecycle.

Senior Delivery Consultant for AWS Professional Services focused on designing, implementing, and managing AI/ML and Generative AI solutions for enterprise customers. This role involves leading project teams, hands-on development, MLOps, and advising customers on cloud AI/ML architectures using AWS services.

Senior Applied Scientist role focused on building and deploying large-scale machine learning systems for fraud and risk prevention in an e-commerce environment. The role involves leading scientific strategy, defining roadmaps, designing and deploying ML solutions, and leveraging GenAI/LLM technologies. It requires experience in real-time production environments, ML modeling, and translating scientific trends into production solutions.

Manager for a Data Science team focused on optimizing outbound communications for millions of customers using AI/ML, including LLMs and RL. The role involves leading the development of personalized messaging strategies, designing experiments, building propensity models, driving AI transformation in data accuracy and reporting, and owning financial planning frameworks. It also includes hiring, mentoring, and cross-functional partnership.

Software Development Engineer on the Sponsored Products and Brands Off-Search team, focused on building hyper-scale systems and data pipelines leveraging Generative AI and LLMs to improve advertising and shopping experiences. The role involves designing and delivering scalable solutions for ad retrieval, allocation, and recommendations, transforming these into personalized and contextually aware parts of the customer journey.

Applied Scientist II role focused on developing and implementing machine learning and causal inference models for Amazon's advertising incrementality measurement. The role involves end-to-end model development, improving existing solutions, and collaborating with product and engineering teams to bring solutions to production. The team builds scientifically-rigorous causal inference methodologies at scale to help customers understand the impact of advertising.

Applied Scientist role at Amazon Ads focused on developing and productionizing end-to-end measurement solutions using Generative AI, classical ML, Causal Inference, NLP, and Computer Vision to provide insights and automate workflows for advertisers.

Senior Applied Scientist role focused on developing and productionizing AI/ML models for ad measurement and performance analysis within Amazon Ads. The role involves end-to-end solution development, leveraging Generative AI, classical ML, NLP, and Computer Vision to provide insights and automate workflows for advertisers. Responsibilities include model development, experimentation, collaboration with engineering and business teams, and mentoring junior scientists.

Software Development Engineer II role focused on building next-generation AI-powered pricing systems for Amazon's digital products. The role involves processing millions of prices daily using advanced AI models like LLMs and GenAI, working with AWS infrastructure, and designing distributed systems at scale.

Software Development Engineer II role focused on building next-generation AI-powered pricing systems for Amazon's digital products. The role involves processing millions of prices daily using advanced AI models like LLMs and GenAI, working with AWS infrastructure, and designing distributed systems at scale.

Software Development Engineer II role focused on building next-generation AI-powered pricing systems for Amazon's digital products. The role involves processing millions of prices daily using advanced AI models like LLMs and GenAI, working with AWS infrastructure, and designing distributed systems at scale.

Software Development Engineer II role focused on building next-generation AI-powered pricing systems for Amazon's digital products. The role involves processing millions of prices daily using advanced AI models like LLMs and GenAI, working with AWS infrastructure, and designing distributed systems at scale.

Senior Applied Scientist role focused on developing and productionizing AI/ML models for ad measurement and performance analysis within Amazon Ads. The role involves end-to-end solution development, leveraging Generative AI, classical ML, NLP, and Computer Vision to provide insights and automate workflows for advertisers. Responsibilities include model development, experimentation, collaboration with engineering and business teams, and mentoring junior scientists.

Applied Scientist role focused on building production ML infrastructure for customer analytics, including offline training pipelines, online scoring systems, and monitoring. The role involves signal analysis, pattern discovery, and predictive modeling, with a focus on behavioral signals from AI agents and agentic workflows, aiming to ship AI-augmented customer experiences.

Senior Applied Scientist role focused on building and deploying ML models for customer analytics and segmentation within AWS. The role involves contributing to customer understanding through segmentation models, behavioral classifiers, and predictive frameworks, with a strong emphasis on taking models from research to production. It requires building production ML infrastructure, framing new modeling problems, and collaborating with engineering teams to integrate ML systems into the CLARA platform and other frameworks. The role also involves contributing to scientific direction, mentoring, and documentation, with a focus on shipping models at scale and adapting to evolving customer behaviors driven by AI and agentic workflows.

This role leads a multi-disciplinary team of applied scientists and engineers focused on developing and deploying generative AI technologies for Amazon's Sponsored Products and Brands. The team works on complex engineering, optimization, and user-experience problems to deliver relevant product ads, driving both shopper experience and business monetization. Responsibilities include leading ML projects, building and deploying models, running experiments, establishing scalable processes, and researching new ML approaches.

This role focuses on designing and building machine learning solutions to enhance customer awareness and product discovery for Amazon's Private Brands. It involves end-to-end project management from ideation to launch, utilizing methods like NLP, deep learning, reinforcement learning, and causal inference. The scientist will work closely with engineering and business teams to solve complex problems and drive measurable business impact.

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.

Senior Delivery Consultant for AWS Professional Services focusing on AI/ML solutions for customers in the ASEAN region. The role involves advising customers on ML possibilities, designing and implementing scalable ML solutions on AWS, leading customer engagements from pre-sales to delivery, and conducting workshops to identify business value through machine learning.

Senior Software Development Engineer role focused on developing innovative solutions in brand measurement for Amazon Ads, leveraging generative AI and machine learning to optimize advertising performance and provide AI-driven insights to advertisers.