This role focuses on building and improving machine learning models for Amazon's vertical search, specifically developing new ranking features and techniques. The scientist will be responsible for the full development cycle, from design and implementation to A/B testing and production deployment, aiming to enhance search quality and effectiveness across Amazon's product ecosystem.

Applied Scientist role focused on building and deploying end-to-end machine learning solutions to prevent eCommerce fraud and manage transaction safety within Amazon's production environment. The role involves innovating with GenAI/LLM/VLM technologies, analyzing large datasets, and creating automated risk evaluation and operational systems.

This role focuses on the operational excellence and reliability of a fleet of ML accelerators and server products, specifically Amazon's Trainium chips. The engineer will be responsible for debugging hardware and software issues, developing automation, analyzing fleet data, and ensuring the health and performance of the ML hardware infrastructure. This is an engineering role focused on the operational aspects of serving ML hardware.

This role focuses on applying machine learning and AI to predict and reconcile product measurements for Amazon's third-party marketplace, impacting fee strategy and seller experience. The scientist will design, develop, and deploy AI/ML models, working closely with engineering and product teams to productionize solutions and validate their business impact through rigorous experimentation.

Software Development Manager leading a team to build and deliver core infrastructure components for AI agents in Amazon Ads. This includes an agent-builder SDK, development tools, and a managed runtime, focusing on scalability, low-latency, and integration with Ads services and foundational models. The role bridges distributed systems, ML infrastructure, and developer tooling.

Senior Data Engineer role focused on building and maintaining data infrastructure for AI-powered insights within Amazon's Fulfillment by Amazon (FBA) division. The role involves architecting data lakes, migrating architectures, establishing metadata management, designing data ingestion patterns, creating a centralized metrics repository, implementing data quality frameworks, designing semantic data models optimized for AI retrieval, developing intelligent orchestration, implementing federated query capabilities, architecting vector database infrastructure, integrating AI-accessible data contracts, and building monitoring frameworks. The position emphasizes the intersection of data engineering and AI, ensuring trustworthy, fast, and scalable GenAI insights.

Applied Scientist role at Amazon Business Ads focusing on building and deploying scientifically novel software solutions for B2B advertising products. Requires experience in model building for business applications and proficiency in Python/deep learning frameworks.

Applied Science Manager for AGI team focusing on quality automation, auditing, and evaluation of LLMs and multimodal systems. Leads a team of scientists to develop quality strategies, auditing frameworks, and research new methodologies to ensure data integrity and model performance. Manages team development, cross-functional communication, and drives research into data impact and utility measurement for AI models.

Applied Scientist role focused on designing, developing, and deploying ML and computer vision models for Amazon's in-store grocery technologies, including smart carts, inventory intelligence, personalization, and store operations. The role involves end-to-end model development from ideation to production, with a focus on solving real-world problems at scale within the grocery domain.

This role focuses on designing and deploying agentic AI systems to automate complex workflows for fraud and abuse detection within Amazon's e-commerce platform. It involves advanced data analysis using SQL and Python, identifying risks, and scaling solutions across the business segment.

This role is for a Sr. AI Solution Architect at AWS who will work with customers to design and implement production-ready generative AI and agentic AI solutions on the cloud. The role involves building technical relationships, advising on AI/ML adoption, and influencing the product roadmap.

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.

Software Development Engineer role focused on building AI/ML-powered products and infrastructure for data integration workflows at Amazon.

This role is for a Senior Applied Science Manager on the Stores Economics and Science team at Amazon. The team uses economics, statistics, and machine learning to understand and design Amazon's buyer and seller economy. The manager will provide structure for complex business problems, work with ML scientists to validate models, and help partners translate analysis into impactful actions. The role requires experience in building large-scale ML/AI solutions, leading scientists, and developing junior talent.

The Applied Scientist will leverage LLMs and generative AI to build automated solutions for seller verification, transaction monitoring, and risk assessment in Amazon's marketplace. The role involves designing, developing, and deploying end-to-end ML solutions to detect and prevent abuse patterns, requiring innovation with the latest GenAI technology and adaptation to evolving threats.

The Language Engineer will develop diverse datasets for training and evaluating Amazon's AI models, utilizing synthetic data generation, model-supported generation, and human-in-the-loop approaches. This role involves designing data collections, analyzing data, building tools for data analysis/creation, and collaborating with scientists and engineers to evaluate AI model performance. Experience with multimodal data and agentic workflows is preferred.

Language Engineer role focused on dataset construction, linguistic annotation, dialog/semantic schemas, and automatic processing of large datasets for AGI Data Services. The role involves designing data collection tasks, analyzing data for insights, building data authoring tools, and collaborating with scientists to evaluate language models.

The Language Engineer will develop diverse datasets for training and evaluating Amazon's AI models, utilizing synthetic data generation, model-supported generation, and human-in-the-loop approaches. This role involves designing data collections, analyzing data, building tools for data analysis/creation, and collaborating with scientists and engineers to evaluate AI model performance. Experience with multimodal data and agentic workflows is preferred.

The Language Engineer will develop diverse datasets for training and evaluating Amazon's AI models, utilizing synthetic data generation, model-supported generation, and human-in-the-loop approaches. This role involves designing data collections, analyzing data, building tools for data analysis/creation, and collaborating with scientists and engineers to evaluate AI model performance. Experience with multimodal data and agentic workflows is preferred.

Senior Prototyping Architect role focused on building functional prototypes using Generative AI, Agentic AI, and other cloud-native architectures. The role involves hands-on coding, architectural decisions for agent behaviors and LLM integrations, and educating customers on AWS services. It requires strong cloud expertise and a passion for experimenting with emerging technologies to solve complex customer problems.

Machine Learning Engineer focused on developing and deploying ML products for network management within Amazon Infrastructure Engineering, aiming to improve customer experience and revolutionize business operations.

Senior Applied Scientist role focused on leveraging generative AI and machine learning to re-imagine advertising experiences for Amazon Ads' Sponsored Products and Brands. The role involves leading ML efforts, analyzing large datasets, building and deploying ML models for insights, traffic monetization, and personalized shopping experiences, and driving end-to-end ML projects. It also includes running A/B experiments, establishing scalable processes, researching new ML approaches, and recruiting/mentoring other scientists.

Applied Scientist II role at Amazon Ads focused on building production ML and bandit solutions to customize the Sponsored Products search experience. The role involves determining ad placement, quantity, and targeting using machine learning, causal inference, and optimization techniques. It emphasizes improving shopper discovery and advertiser reach by modeling shopper responses and optimizing ad allocation and ranking on the search page, with a recent focus on integrating LLMs/GenAI for production use cases.

Senior Robotics Engineer role focused on designing, deploying, and managing advanced robotic systems at scale within AWS data centers. This involves developing robust robotic solutions, collaborating with external partners, and ensuring reliability, efficiency, and scalability. The role requires experience with vision language actuation models and shipping production code.

This role focuses on designing and implementing enterprise-scale Generative AI solutions using AWS services, optimizing performance, and guiding teams in integration. It involves a mix of technical implementation and strategic guidance for AI applications.

The Data Scientist, Digital Acceleration role at Amazon focuses on designing and delivering advanced analytics and machine learning models for Amazon's digital businesses. The role involves end-to-end project management, from ideation to deployment, with a strong emphasis on Generative AI solutions and LLMs to enhance data access and solve customer problems within the Digital Acceleration Analytics team.

Senior Software Development Engineer to build and optimize infrastructure for AI/ML workloads on EC2 Nitro. Focus on performance measurement, benchmarking, regression testing, and influencing future hardware designs for LLMs, multimodal systems, and emerging architectures. Role involves both customer-facing performance problem-solving and foundational infrastructure development.

Software Development Engineer to build and optimize performance measurement infrastructure for AI/ML workloads on AWS EC2 Nitro. The role involves low-level systems, ML frameworks, and serving layers to translate performance insights into technical requirements for platform designs.

Software Development Engineer to build and optimize performance measurement infrastructure for AI/ML workloads on AWS EC2 Nitro. The role involves low-level systems, ML frameworks, and serving layers to translate performance insights into technical requirements for platform designs.

The Language Engineer will develop diverse datasets for training and evaluating Amazon's AI models, utilizing synthetic data generation, model-supported generation, and human-in-the-loop approaches. This role involves designing data collections, analyzing data, building tools for data analysis/creation, and collaborating with scientists and engineers to evaluate AI model performance. Experience with multimodal data and agentic workflows is preferred.

Software Development Engineer II role focused on building the TFS platform for Amazon Transportation, incorporating Agentic AI systems, anomaly detection, and financial insights. The role involves designing and delivering algorithms and infrastructure for accounting transportation costs at scale, with a focus on financial reconciliation and month-end close acceleration.

Senior AI Solution Architect for AWS, focusing on guiding enterprise customers in adopting and scaling GenAI/ML and Agentic technologies. The role involves designing scalable architectures, acting as a trusted advisor, and contributing to product roadmaps by translating customer needs into technical solutions. Responsibilities include hands-on deep dives, workshops, and creating technical content.

Applied Scientist role focused on developing and launching AI solutions for Prime Video's search and personalization systems, involving deep learning, GenAI, and reinforcement learning. The role requires end-to-end ownership from design to launch, including experimentation and evaluation, with a strong emphasis on delivering customer-facing products. Research publication is also a component.

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.

Applied Scientist II at Amazon focused on improving shopping experiences using LLMs. Requires 3+ years of building models for business applications, a PhD or Master's with 4+ years of experience, and a publication/patent record. Experience with algorithms, data structures, optimization, data mining, and parallel computing is expected.

Manager for a Language Engineering team focused on data production and processing for AI and LLMs. Responsibilities include team leadership, technical guidance, process optimization, and collaboration with science and tech partners.

The AI Specialist SA team builds technical relationships with customers of all sizes and operate as their trusted advisor, ensuring they get the most out of the cloud at every stage of their journey while adopting GenAI/ML and Agentic technologies across their organisation. You’ll manage the overall technical relationship between AWS and our customers, making recommendations on security, cost, performance, reliability and operational efficiency to accelerate their challenging GenAI/ML and Agentic projects.

Applied Scientist role at Amazon Prime Video focusing on Playback Intelligence. The role involves using applied machine learning and data science, with specializations in video streaming optimization, information retrieval, anomaly detection, root-causing systems, large language models, and generative AI across various modalities. Responsibilities include translating business requirements into deliverables, improving customer playback quality, reducing time/cost/effort for optimization and defect mitigation, and integrating new algorithms into modeling stacks. The role emphasizes working backwards from desired outcomes to determine ideal solutions.

Senior Software Development Engineer to drive the technical direction of the Catalog & Events services within the Workshop Studio platform, focusing on building AI-powered agentic systems for content discovery, participant guidance, automated summaries, and agent-assisted authoring. The role also involves developing multi-tenant platform infrastructure, integration APIs, and evolving the authentication architecture, with a strong emphasis on technical leadership and operational excellence.

Applied Scientist role focused on building and improving machine learning models for buyer risk prevention at Amazon. This involves analyzing large datasets, developing and deploying models, and collaborating with engineers and business teams to safeguard transactions and enhance risk policies. The role also includes experimenting with Generative AI and LLMs for automation and risk evaluation.

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.

Software Development Engineer III on the Alexa 3P Experiences team, focusing on building consumer-facing generative AI experiences with third-party partners using LLMs and agentic capabilities. The role involves leading design and architecture, owning technical vision for SDKs, and driving engineering best practices.

Software Development Engineer III on the Alexa 3P Experiences team, focusing on building consumer-facing experiences with third-party partners using generative AI, LLMs, and agentic capabilities. The role involves leading design and architecture of experiences and SDKs, taking a long-term system view, and mentoring engineers.

Software Development Engineer II on the Alexa 3P Experiences team, focused on building consumer-facing generative AI experiences using LLMs and agentic capabilities with third-party partners. The role involves designing and developing scalable solutions, contributing to category scaling frameworks, and driving engineering best practices.

Software Development Engineer role focused on building and managing machine learning models and platforms for fraud prevention and risk management at Amazon scale. The role involves developing self-service capabilities for experimenting with new ML models and managing numerous risk use cases globally, operating at the intersection of Machine Learning and Security.

Machine Learning Engineer to build and deploy agentic AI products within AWS Applied AI Solutions. The role involves transforming research into production systems, owning end-to-end deployment, and establishing scalable ML processes.

This role focuses on building and deploying advanced machine learning models for consumer business applications, optimizing business operations and profitability. It involves end-to-end ownership from data analysis and model development to implementation and scaling, with a strong emphasis on creating automated processes for model lifecycle management.

Solutions Architect role focused on driving adoption of AWS cloud solutions for Consumer Packaged Goods (CPG) companies, with a specific emphasis on Generative AI and Agentic AI. The role involves understanding CPG business challenges, architecting cloud solutions, educating customers on AWS capabilities, and helping them navigate the shift towards AI-driven operations and autonomous agents. This includes driving adoption of GenAI for demand forecasting, agentic ERP exception handling, and supply chain analytics, as well as building relationships with stakeholders and advocating for CPG-specific product needs.