Amazon

The Applied Scientist will develop and maintain LLM-as-a-Judge systems and auditing frameworks to ensure the quality of data used for training and evaluating Amazon Nova models, impacting LLM products and services.

Applied Scientist role at Amazon Prime Video focused on building machine learning systems for content presentation and discovery. The role involves working with multi-modal embeddings, contextualized ranking, reinforcement learning, and recommender systems to improve customer engagement with the Prime Video catalog.

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.

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.

Applied Scientist role at Amazon Prime Video focusing on content reasoning, enrichment, and localization. The role involves research and application of machine learning, audio processing, and natural language understanding, with specific mention of multimodal machine translation, speech synthesis, speech analysis, and asset quality assessment. Requires experience in building models for business applications and a PhD or Master's degree. Familiarity with foundational models and speech synthesis is a plus.

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.

AI Product Manager - Technical for Amazon Customer Service, focusing on end-to-end lifecycle of large-scale AI products using Generative AI, ML, NLP, Agentic AI, and Multi-Agent Architectures to transform customer experience.

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.

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.

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.

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 III role focused on designing, developing, evaluating, deploying, and updating data-driven models and analytical solutions for machine learning and natural language applications. The role involves applying statistical modeling, optimization, and ML techniques, building and deploying models in production, and researching novel ML approaches. Requires a Master's degree (or equivalent experience) in a related field and experience in programming and developing supervised/unsupervised ML models.

Principal Technical Product Manager to lead the strategy and execution of an end-to-end agentic core infrastructure (SDK, Runtime, Builder Tools) that enables agent and skill builders to develop, test, and operate production-grade agentic experiences at scale. This role will innovate leveraging and extending AWS core primitives like Agent Core to fulfill Amazon Ads specific needs like agent authorization, guardrails, shared memory, and fully managed runtime for complex multi-step reasoning and multi-agent workflows.

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.

This role is for a Principal AI Creative Director focused on building a generative AI system for Amazon Ads. The core responsibility is to act as the 'human judgment layer', defining and decomposing creative direction, brand intelligence, and quality standards into machine-readable primitives. This involves leading the systemization of taste, defining aesthetic moderation frameworks, and building prototypes to shape AI-powered creative experiences for advertisers. The role requires deep fluency in AI creation tools and the ability to translate creative vision into system requirements, influencing design, engineering, and product leadership.

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 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 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.

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.

Principal Product Manager for Prime Video's Personalization and Monetization, focusing on ML-powered features, recommendation systems, and customer experience. This role involves defining product strategy, translating business problems into algorithmic requirements, and guiding the ML lifecycle to ship scalable, customer-centric AI features.

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.

Software Development Engineer II, Post Silicon Validation for AWS's next-generation machine learning accelerators. This role involves validating the complete vertical stack of ML accelerators, from silicon to system, ensuring quality and performance for AWS cloud infrastructure. Responsibilities include developing validation strategies, executing test plans, hardware bring-up and debug, and collaborating with cross-functional teams.

Applied Scientist role focused on building and evaluating ML models for life sciences applications, specifically protein biology. Requires a PhD in a related field and expertise in ML/deep learning, with a preference for publication experience.

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.

Software Development Engineer III for Amazon's Sponsored Products and Brands team, focusing on building conversational ad experiences powered by LLMs. The role involves developing large-scale, low-latency distributed systems, ML infrastructure, LLM-based AI workflows, and contributing to LLMOps, with a focus on customer-facing functionality impacting millions of shoppers.

This role focuses on building and presenting generative AI demonstrations for AWS customers, educating them on AI technologies and providing architectural guidance for solutions involving AWS services and partner offerings. The role involves creating industry-grade demos, delivering compelling tours, and facilitating hands-on experiences to drive customer engagement and pipeline opportunities.

Applied Scientist role focused on developing and productizing AI solutions for enterprise services within AWS. The role involves designing and implementing ML systems for diverse applications, creating scalable algorithms, conducting experimentation with advanced techniques (LLMs, CV, agentic AI), and collaborating with engineering and product teams to deliver customer impact. The primary output is shipped AI products, with a secondary focus on agentic AI systems.