This role focuses on building and deploying machine learning models to improve customer experience through personalized recommendations on Amazon's retail website. The scientist will leverage large-scale data and computing resources to understand customer behavior, develop state-of-the-art recommendation models, and measure their impact on the business.

Seeking a Senior Research Scientist to lead the design and implementation of autonomous experimental research platforms leveraging data science and AI for sustainable materials innovation. This role combines Physical AI with materials chemistry to accelerate discovery and validation, establishing scientific strategy and technical roadmaps for next-generation autonomous capabilities.

The role focuses on building the AI/ML foundation for sustainability initiatives, involving data identification, ingestion, harmonization, storage, and maintenance of strategic models and data. It requires developing data pipelines, implementing data collection strategies, and creating monitoring and alarming systems for sustainability-related AI solutions.

This role focuses on building the AI/ML foundation for sustainability initiatives, involving data and AI/ML infrastructure implementation, data pipeline development, and establishing ML Ops best practices. The goal is to support various sustainability efforts like carbon footprinting and climate risk monitoring.

Applied Scientist role focused on building next-generation software verification tools by combining AI, cloud computing, and formal verification expertise. The role involves understanding customer needs, identifying tools and methods for verification, and exploring generative AI techniques for requirements formalization, test generation, and proof repair.

This role focuses on architecting and implementing AI solutions, specifically agentic AI, within Amazon Connect for enterprise customers. It involves guiding customers on model selection, prompt configuration, tool integration, and ensuring customer data is ready for AI agents. The role is hands-on, requiring coding, integration building, and collaboration with customer teams to move solutions from proof-of-concept to production.

This role focuses on inventing and implementing scientific solutions, including machine learning models, for EC2 capacity intelligence. It involves developing and productionizing data-driven solutions for efficient capacity and demand allocation, aiming to improve customer experience. The role requires expertise in ML/DL and applying scientific principles to real-world business challenges, with a strong emphasis on bridging science and engineering.

Data Scientist role focused on building predictive models and optimization algorithms for AWS Support capacity planning. The role involves forecasting contact and volume, identifying business opportunities using statistics and machine learning, and partnering with various teams to drive operational improvements. Requires experience in data science, forecasting, optimization, and machine learning, with a focus on applying theoretical models in an applied environment using Python or R.

Software Engineer role on the Ads Marketing team, focusing on building an AI-powered marketing intelligence engine (MCC) that uses autonomous AI agents for campaign management. The role involves designing, developing, and deploying production-grade ML systems, owning AI/ML pipelines, and collaborating with Applied Scientists. The system aims to automate repetitive tasks and improve campaign execution time.

Senior Applied Scientist role focused on designing, implementing, and scaling decision-making algorithms for AWS EC2 capacity management. The role involves mathematical optimization, large-scale problem solving, and applying ML/Gen AI methods to enhance optimization algorithms. Responsibilities include data analysis, prescriptive optimization modeling, simulation, A/B testing, and collaborating with engineering and product teams.

Senior Business Intelligence Engineer focused on building and scaling personalized recommendations for millions of customers in EU marketplaces. The role involves developing custom models (embeddings, persona matching) using Python and Spark, building production-grade Python services, serverless infrastructure (AWS Lambda, CDK), and APIs (FastAPI) for marketing teams. It also includes owning reporting, measurement, and deep-dive analytics for personalized marketing campaigns.

Senior Research Scientist role focused on building and validating AI models to quantify the impact of Amazon's operational presence on local communities. The role involves designing causal frameworks, predictive models, and automated causal discovery systems using LLMs and document understanding. It also includes deploying production ML forecasting systems with multi-modal data sources and mentoring junior scientists. The work is at the intersection of computational social science, AI, and operational planning, influencing decisions affecting thousands of communities daily.

This role focuses on prompt engineering for Generative AI and LLMs, involving the full prompt lifecycle from concept to production. Responsibilities include developing Python code, managing CI/CD pipelines, architecting contextual frameworks, and testing prompts to enhance AI performance and address real-world challenges like counterfeit detection within the Trustworthy Shopping Experience team.

The Senior Product Manager-Tech will own the vision for merchant retail operations and the agentic platform that enables both internal teams and customers to optimize revenue and operations through AI-powered experiences. This role requires deep understanding of retail systems and the ability to navigate complex integration challenges while maintaining a strategic focus on scaling autonomous retail operations globally.

This role focuses on ensuring the quality and reliability of AI model evaluations for Amazon's Seller Assistant copilot. The primary responsibilities involve benchmarking AI models, evaluating audits performed by a core auditing team, improving audit consistency, and enforcing quality standards. The goal is to scale AI model evaluation coverage and ensure high-quality outcomes for sellers.

This role focuses on ensuring the quality and reliability of AI model evaluations for Amazon's Seller Assistant copilot. The primary responsibilities involve benchmarking AI models, evaluating audits performed by a core auditing team, improving audit consistency, and enforcing quality standards. The goal is to scale AI model evaluation coverage and ensure high-quality outcomes for sellers.

This role focuses on ensuring the quality and reliability of AI model evaluations for Amazon's Seller Assistant copilot. The primary responsibilities involve benchmarking AI models, evaluating audits performed by a core auditing team, improving audit consistency, and enforcing quality standards. The goal is to scale AI model evaluation coverage and ensure high-quality outcomes for sellers.

This role focuses on building next-generation software verification tools by combining AI, cloud computing, and formal methods. The scientist will explore generative AI techniques for formalizing requirements, generating tests, and repairing proofs, and will work on agentic systems to ensure AI agents operate within safety boundaries.

This role focuses on prompt engineering for Generative AI and LLMs, involving the full prompt lifecycle from concept to production. Responsibilities include developing Python code, managing CI/CD, architecting contextual frameworks, and testing prompts to enhance AI performance and address real-world challenges, specifically within the Trustworthy Shopping Experience team at Amazon.

Senior Applied Scientist role focused on developing evaluation frameworks and data collection protocols for robotic capabilities. The role involves designing how to measure, stress-test, and improve robot behavior, building infrastructure for teleoperation, evaluation, and learning, and analyzing results to identify performance gaps. It requires expertise in robotics, ML, and human-in-the-loop systems, with a focus on turning capability goals into measurable evaluation systems.

This role focuses on designing and implementing intelligent automation solutions using AI, ML, LLMs, and RPA tools within Amazon's Accounts Receivable team. The engineer will optimize existing automations, partner with stakeholders, lead projects, and ensure reliability and integration across financial systems. Basic qualifications include RPA certifications, programming experience (Python/C#), and experience with RPA tools and APIs. Preferred qualifications involve deploying AI products at scale, data mining, and integrating LLMs with enterprise data using embeddings and vector search.

Software Development Engineer role focused on building conversational ad experiences using LLMs within Amazon's advertising business. The role involves driving product and engineering initiatives, building large-scale, low-latency distributed systems, ML infrastructure, data pipelines, and implementing LLM models in production, including LLMOps.

Software Development Engineer II role focused on architecting and delivering AI-powered design automation solutions for AWS's global data center infrastructure, integrating BIM platforms and AWS services. The role involves productionizing ML models, implementing human-in-the-loop workflows, and collaborating with applied scientists and domain experts.

Software Development Engineer II role focused on building generative AI applications for data center design automation within AWS Infrastructure Services. The role involves architecting and implementing scalable production systems that integrate BIM platforms, cloud services, and AI technologies, with a focus on human-in-the-loop workflows. The engineer will collaborate with applied scientists to productionize ML models and mentor junior engineers.

Senior Applied Scientist role focused on developing and improving sensing systems for advanced robotics at Amazon scale. This involves designing custom sensor systems, integrating AI and control systems, and working from concept to production in a fast-paced, interdisciplinary environment. The role requires deep knowledge in sensing, signal processing, computer vision, and machine learning, with a focus on shipping robotic products.

Senior Software Development Engineer role within AWS Commercial Application Services focusing on building cloud infrastructure for enterprise applications, specifically SAP workloads. The role involves leveraging Agentic AI and Generative AI to enhance operational efficiency, redefine cloud computing, and create new capabilities for customers. It requires designing and scaling mission-critical services, influencing product strategy, defining system architecture, and ensuring customer needs are met through AI-driven solutions. The position emphasizes building large-scale distributed systems integrated with AI capabilities.

This role focuses on integrating computer vision, edge computing, and physical automation systems to enable real-time operational intelligence, improve equipment performance, and optimize process flow within global fulfillment networks. The engineer will bridge AI/ML models with physical systems, leading the development and deployment of sensor-driven automation solutions and ensuring seamless integration across hardware, software, and control layers.

Senior Software Engineer role focused on building and enhancing AWS Bedrock AgentCore services within the Agentic AI field. The role requires developing scalable, efficient, and fault-tolerant machine learning powered solutions, with a preference for experience in ML systems. Responsibilities include delivering strategic technical projects, designing new software systems, mentoring engineers, and providing technical leadership in a fast-moving, startup-like environment within a large company.

Senior Software Engineer role at AWS EC2 focusing on building enterprise cloud infrastructure services that leverage Agentic and Generative AI for SAP workloads. The role involves designing, scaling, and integrating AI-driven innovations to enhance operational efficiency and customer experience, with a strong emphasis on autonomous systems and intelligent automation.

Software Development Engineer role focused on building a new AWS service for agentic AI, specifically enabling memory capabilities for autonomous agents. The role involves designing, developing, and deploying large-scale, fault-tolerant ML systems, collaborating with applied scientists, and mentoring junior engineers.

Senior Applied Scientist role focused on developing and deploying large-scale machine learning systems for fraud and risk prevention in an e-commerce environment. The role involves leading scientific strategy, designing and deploying ML systems, and leveraging Generative AI and LLMs to build next-generation platforms. It requires experience in building ML models, deep learning, and programming languages.

This role focuses on building and deploying advanced machine learning models for Amazon's consumer businesses in India and other emerging markets. The scientist will analyze large datasets, develop and evaluate scalable ML solutions, and work closely with engineering teams to implement these models in production. The role involves end-to-end ownership of business problems and directly impacting profitability.

This role focuses on applying and researching novel machine learning approaches, particularly deep learning methods for multi-objective optimization, to develop real-time algorithms for allocating billions of ads daily in advertising auctions. The work involves end-to-end ML projects with ambiguity and scale, aiming to improve customer experience and drive revenue. The role also involves recruiting and mentoring scientists.

Applied Scientist role at Amazon Ads focusing on generative AI for sponsored products, developing real-time ML algorithms for ad allocation and multi-objective optimization. The role involves end-to-end ML projects with ambiguity and scale, aiming to improve customer experience and drive revenue. It also includes researching new ML approaches and potentially recruiting/mentoring scientists.

This role focuses on ensuring the quality and reliability of AI model evaluations for Amazon's Seller Assistant copilot. The primary responsibilities involve benchmarking AI models, evaluating audits performed by a core auditing team, improving audit consistency, and enforcing quality standards. The goal is to scale AI model evaluation coverage and ensure high-quality outcomes for sellers.

This role focuses on ensuring the quality and reliability of AI model evaluations for Amazon's Seller Assistant copilot. The primary responsibilities involve benchmarking AI models, evaluating audits performed by a core auditing team, improving audit consistency, and enforcing quality standards. The goal is to scale AI model evaluation coverage and ensure high-quality outcomes for sellers.

This role focuses on ensuring the quality and reliability of AI model evaluations for Amazon's Seller Assistant copilot. The primary responsibilities involve benchmarking AI models, evaluating audits performed by a core auditing team, improving audit consistency, and enforcing quality standards. The goal is to scale AI model evaluation coverage and ensure high-quality outcomes for sellers.

Senior Applied Scientist role at Amazon Prime Video focused on developing and launching AI solutions for personalization and discovery, including search systems. The role involves end-to-end ownership of machine learning models, from design and implementation to experimentation and evaluation, with a focus on benefiting millions of customers. The position also requires staying updated with the latest modeling techniques and publishing research findings.

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.

Senior Applied Scientist role focused on building predictive intelligence for capacity management in AWS workspaces. This involves developing ML systems for demand forecasting, resource optimization, and cost efficiency at enterprise scale. The role requires translating business needs into production ML systems, designing algorithms, and applying advanced ML techniques like time-series forecasting, reinforcement learning, and causal inference. Emphasis on low-latency, large-scale data processing, and collaboration with product and engineering teams.

ML Compiler Engineer II on the Neuron Compiler Automated Reasoning Group, developing and maintaining tooling for fuzzers and specification synthesis for an LLVM-based compiler targeting ML accelerators (Inferentia/Trainium) for domains like Large Language and Vision. Focus on accuracy and reliability of the compiler stack.

Applied Scientist II role focused on leveraging GenAI/LLMs to build agentic solutions for financial insights and actions within Amazon. The role involves developing AI trust and safety in the financial domain, creating training/evaluation datasets for fine-tuning, and collaborating with engineers for productionalization. It balances scientific research with production deployment, with opportunities for external publications.

Sr. Applied Scientist role focused on developing and implementing AI/ML solutions to improve the Amazon Selling Partner experience. This involves building scalable models, analyzing data, and staying current with LLM, RL, and agent-based AI research to translate findings into practical applications. The role requires strong ownership of the full project lifecycle and collaboration with business and engineering teams.

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 at Amazon Ads focusing on measurement science, developing solutions for performance measurement products, sales impact analysis, and AI tools for customer insights and workflow automation. The role involves end-to-end ownership of measurement solutions, from design to production, leveraging Generative AI, classical ML, Causal Inference, NLP, and Computer Vision.

This role bridges generative AI research and visual storytelling for Prime Video, focusing on translating ML capabilities into production workflows and understanding creative needs. The Sr. Design Technologist will assess generative models, build proof-of-concept tools, and identify gaps between model output and production requirements.

Software Development Engineer role focused on building core functionality for AWS Internet Monitoring service, leveraging Generative AI techniques for network monitoring, traffic engineering, and autonomous systems. The role involves designing, developing, and deploying AI-integrated software systems, collaborating with cross-functional teams, and ensuring operational excellence.

MS or PhD student internship in machine learning, deep learning, generative AI, LLMs, speech technology, robotics, computer vision, optimization, operations research, quantum computing, automated reasoning, or formal methods. Focus on inventing, designing, and implementing state-of-the-art solutions. Will own design and development of end-to-end systems, write technical white papers, create roadmaps, and drive production-level projects. Opportunity to design new algorithms and models, and deploy them into production.