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.

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.

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

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

Software Development Manager for Amazon's Devices & Services Trust CX Innovations team, focusing on building and scaling teams that deliver privacy-first, accessible, and trustworthy AI experiences for consumer devices like Alexa and Echo. The role involves driving technical strategy for privacy-preserving AI architectures, responsible AI frameworks, and accessibility features, while balancing performance with privacy, building explainable AI systems, and creating guardrails for LLMs. Key challenges include latency vs. privacy trade-offs, AI safety at scale, ambient computing privacy, multimodal AI systems, and real-time evaluation.

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.

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.

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.

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.

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.

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 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.

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 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.

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.