Amazon has 1472 active AI-related job listings. The company is heavily focused on roles within the "agents" stage, which accounts for 38% of its AI hiring, followed by "application" at 26%. Engineering is the dominant function, with 1172 positions. Over the last 30 days, Amazon has added 667 new AI roles, representing a 74% increase compared to the previous 30-day period. Frequent tech tags include agent_orchestration, model_serving, and multimodal.
Currently tracking 1110 active AI roles, down 16% versus the prior 4 weeks. Primary focus: Agent · Engineering. Salary range $65k–$465k (avg $194k).
Amazon currently has 1573 active AI-related roles in our index. The most common open titles are: ML Data Associate-II (9), 2026 Applied Scientist Intern, Amazon University Talent Acquisition (8), AI Data Associate (Dutch) , Artificial General Intelligence Data Services (8), Software Development Engineer, AWS (8), Senior Delivery Consultant - Data , Professional Services, AWSI HCLS (7). Most positions are in Engineering and Research.
Amazon's active AI hiring is concentrated in: agents (41%), application (26%), serving infrastructure (13%). These categories follow a seven-stage AI lifecycle: data, pre-training, post-training, serving infrastructure, agents, evaluation, and application.
Amazon is hiring AI talent in: United States (1023 roles), Canada (59 roles), United Kingdom (47 roles), India (23 roles).
Job postings at Amazon most frequently mention: Machine Learning, Generative AI, Large Language Models (LLMs), Software Engineering, Agentic Systems.
In the past 30 days, Amazon has posted 696 new AI-related roles.
| Title | Stage | AI score |
|---|---|---|
| Machine Learning Engineer II , AGI Customization Machine Learning Engineer II on the AGI Customization team at Amazon, focusing on developing and optimizing LLM training techniques, including fine-tuning, distillation, model evaluation, and prompt optimization for multimodal LLMs and Generative AI solutions. | Post-trainData | 8 |
| Software Development Engineer (ML), AGI Customization, AGI Customization ML Engineer role focused on developing customization capabilities like fine-tuning and distillation for LLMs, advancing LLM training techniques, and optimizing multimodal LLMs and Generative AI solutions. Requires experience deploying LLMs in production and knowledge of ML frameworks. | Post-trainServe |
| 8 |
| Senior Applied Scientist, Translation Services Senior Applied Scientist role focused on applying advanced NLP and LLM techniques to improve machine translation quality and pipeline efficiency for Amazon's e-commerce platform. The role involves architecting and implementing scalable ML solutions, driving data analysis, and pioneering modeling techniques for translation quality assessment and optimization. The scientist will also serve as an expert in LLM applications for translation and mentor team members. | Post-train | 8 |
| Sr. Applied Scientist, SSG Science This role focuses on optimizing and fine-tuning Generative AI models for edge platforms, working closely with custom ML hardware. The scientist will train custom models, analyze deep learning workloads, and collaborate with cross-functional teams to build ML-centric solutions for consumer devices. The role also involves publishing research and presenting at ML conferences. | Post-trainServe | 8 |
| Senior Applied Scientist, LLM Code Agents, Kiro Science Senior Applied Scientist role focused on advancing LLM code intelligence through reinforcement learning and post-training methodologies, with a strong emphasis on research, publication, and deploying these models into production systems for developers. | Post-trainAgent | 8 |
| Sr. Software Engineer- AI/ML, AWS Neuron Distributed Training - Performance Optimization Senior Software Engineer focused on performance optimization for distributed AI model training on AWS Trainium accelerators. The role involves working with frameworks like PyTorch and JAX, optimizing the Neuron software stack, and improving training throughput and efficiency for large-scale models. | Post-trainServe | 8 |
| Principal Applied Scientist, Alexa International Tech The Principal Applied Scientist role at Amazon's Alexa International team focuses on defining research directions, inventing and applying ML techniques, conducting experiments, publishing results, and translating research into practice for expanding Alexa's reach across countries, languages, devices, and cultures. The role requires a PhD in AI/ML/NLP with 10+ years of experience, a strong publication record, and expertise in building and deploying ML solutions at scale. | Post-train | 8 |
| Delivery Consultant- AI/ML, WWPS ProServe Delivery Team This role focuses on designing, implementing, and scaling AI/ML solutions for enterprise customers on AWS, with a strong emphasis on generative AI. The consultant will work with customers to identify use cases, select, fine-tune, and deploy models, and provide technical guidance throughout the project lifecycle. | Post-trainAgent | 7 |
| Applied Scientist, SCOT Forecasting and Labs - CIV Team Applied Scientist role focused on developing and prototyping new statistical, causal, and machine learning techniques for inventory availability and delivery speed estimations in Amazon's retail supply chain. The role involves collaborating with software teams for production implementation and analyzing business metrics. | Post-train | 7 |
| Applied Scientist II, Central Machine Learning The Applied Scientist II role focuses on building and deploying machine learning models for Amazon's consumer businesses. Responsibilities include analyzing large datasets, designing, developing, evaluating, and deploying scalable predictive models, and implementing novel ML approaches. The role involves collaborating with engineering teams for real-time implementation and establishing automated processes for model development and validation. The position requires a PhD or Master's degree with significant experience in ML and programming, and a track record of patents or publications. | Post-trainServe | 7 |
| Data Science I, SCOT Forecasting & Lab This role focuses on improving existing machine learning methodologies within Amazon's supply chain optimization team. The Data Scientist will analyze large datasets, develop and test model enhancements, fine-tune parameters, and formalize assumptions about model behavior. They will also contribute to the research community by publishing papers and collaborating with other scientists and academic researchers. The role requires strong analytical and communication skills to interface with business customers and stakeholders. | Post-train | 7 |
| Applied Scientist, Amazon Redshift Research scientist to build deep learning models for predicting query resource consumption in Amazon Redshift, covering the full ML lifecycle from data analysis to production deployment and publication. | Post-trainServe | 7 |
| Business Research Analyst, ARTS This role involves developing and implementing ML/LLM solutions for business needs within Amazon's Global Stores division. The analyst will collaborate with experts, drive product pilots, build scalable solutions, write code, develop ML/LLM models, and optimize solutions by coordinating between science and software teams. The role requires working independently in ambiguous, fast-paced environments with ML/LLM models. | Post-train | 7 |
| Applied Scientist, Prime Video - Content Localization, Understanding & Enrichment This role focuses on research and development of speech and audio generation technology, including end-to-end speech-to-speech architecture and audio processing solutions. The scientist will define research roadmaps, publish findings, and develop deep learning algorithms, with a focus on computer vision algorithms. The role involves building models for business applications and potentially mentoring/hiring other scientists. | Post-trainData | 7 |
| Sr Manager, International Shopping AI Product, Alexa for Shopping Senior Manager, Product Management, AI Shopping, International to lead a team of Product Managers and Editors who help train AI models to deliver helpful, delightful conversational experiences for customers. This role advocates for and supports product parity efforts across international marketplaces by evaluating features pre-release and producing locally relevant insights to guide refinements. They guide efforts to automate evaluations, tune prompts, and localize experiences, enabling our AI Shopping initiatives to scale internationally. The team delivers delightful, locally relevant conversational experiences through LLM data curation and editing, evaluation, and prompt engineering. | Post-trainData | 7 |
| Data Scientist II, Amazon Currency Convertor Data Scientist II at Amazon Payments focused on building analytical solutions for the Amazon Currency Convertor using Gen AI, LLM, and other machine learning techniques for text analytics, segmentation, and prediction. Responsibilities include applying causal inference, developing descriptive and predictive solutions, collaborating with stakeholders, innovating with modeling techniques, performing exploratory data analysis, and building models using standard techniques. Specific tasks involve fine-tuning Amazon LLMs for text summarization, preventing catastrophic forgetting, feature engineering, and implementing data flow solutions. | Post-train | 7 |
| Business Research Analyst - I, RBS Tech This role involves implementing classical ML models and LLM-based inferences for business problems. The analyst will develop prompts, conduct evaluations, collaborate on deployment, and monitor performance. The role requires hands-on Python and ML/LLM toolkit skills, understanding of AI/ML trade-offs, and the ability to deliver scoped ML components. | Post-trainServe | 7 |
| Business Research Analyst - I, RBS Tech This role involves implementing classical ML models and LLM-based inferences for business problems. The analyst will develop prompts, conduct evaluations, collaborate on deployment, and monitor performance. The role requires hands-on Python and ML/LLM toolkit skills, understanding of AI/ML trade-offs, and the ability to deliver scoped ML components. | Post-trainServe | 7 |
| Applied Scientist, Amazon Music Applied Scientist role at Amazon Music focusing on building, training, and deploying ML models for customer experiences and business decisions. The role involves collaborating with scientists and engineers, experimenting with modern ML techniques, and implementing scalable data pipelines and model-serving systems. It's suitable for early-career individuals with a PhD or Master's degree and 3+ years of experience in building models for business applications. | Post-trainServe | 7 |
| Senior Audio Applied Scientist, Edge Technology Senior Applied Scientist role focused on audio processing for Echo devices, involving research, development, and commercialization of spatial audio and music processing technologies. Requires expertise in signal processing and C/C++, with preferred experience in ML applications for audio. | Post-trainServe | 7 |
| Applied Scientist II, Advertising Trust Build and develop ML models for content understanding and labeling in Ads, utilizing visual and textual features, scaling to multiple languages and countries. Collaborate with engineers and scientists to build, train, and deploy these models, writing production-level code for ad labeling and moderation. | Post-train | 7 |
| Applied Scientist II, Translation Services Applied Scientist II role focused on building and implementing LLM-based machine learning solutions for language translation at Amazon. The role involves data analysis, applying state-of-the-art modeling techniques, and collaborating with cross-functional teams to improve translation accuracy and efficiency for millions of customers worldwide. | Post-train | 7 |
| Applied Scientist, Prime Video - Content Localization, Understanding & Enrichment Applied Scientist role at Amazon Prime Video focusing on content localization, understanding, and enrichment. The role involves applying NLP and computer vision research to video content, leading a team of applied scientists, and developing roadmaps for research. Requires experience building models for business applications and implementing deep learning algorithms, particularly in computer vision. | Post-train | 7 |
| Applied Scientist, Prime Video - Content Localization, Understanding & Enrichment Applied Scientist role at Amazon Prime Video focusing on content localization, understanding, and enrichment. The role involves applying NLP and computer vision research to video content, leading a team of applied scientists, and developing roadmaps for research. Requires experience building models for business applications and implementing deep learning algorithms, particularly in computer vision. | Post-train | 7 |
| AI Editor, Alexa for Shopping Content and Marketing Experiences This role focuses on improving AI model fluency through human-in-the-loop evaluations and LLM judge audits, developing prompting strategies, creating alignment data for LLMs in shopping use cases, and identifying/mitigating biases through fine-tuning. It involves cross-functional collaboration with Product, Science, and Design teams to enhance customer experience metrics and ensure model improvements for Alexa for Shopping. | Post-trainAgent | 7 |
| Applied Scientist, Full-funnel Agentic Intelligence and Models Applied Scientist role focused on developing core models for Full-funnel Agentic Intelligence and Models within Amazon Advertising. The role involves understanding shopping journeys across ad products and publishers, and partnering with engineers and product managers to productize the work. Requires experience in building models for business applications and a strong publication or patent record. | Post-train | 7 |
| Language Data Scientist, Alexa International This role focuses on analyzing and evaluating conversational interaction data to support the training and evaluation of LLMs and machine learning models for Alexa's speech interfaces. The Language Data Scientist will own data analysis, research requests, and contribute to developing annotation workflows and evaluation conventions. | Post-trainEval Gate | 7 |
| Data Scientist II, PXT Central Science Data Scientist II role focused on applying statistical, machine learning, and 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 creating benchmarks for GenAI model performance. | Post-trainAgent | 7 |
| Applied Scientist Manager, Tax Engine Manage and mentor a team of scientists and engineers focused on applying AI/ML, including language models, for tax classification and calculation within Amazon's global Tax Engine platform. The role involves improving team processes, balancing experimentation with delivery, and partnering with stakeholders to build roadmaps for new products and services, with a focus on predictive and generative AI applications. | Post-trainAgent | 7 |
| Sr. Applied Scientist, Special Projects This role focuses on building and evaluating state-of-the-art ML models for biology and life sciences applications, requiring experience with deep learning methods and programming in languages like Python. The role is part of a special projects team aiming to innovate at scale and bring products to market. | Post-train | 7 |
| Data Scientist II, Long Term Planning and Forecasting This role focuses on developing causal inference models, automated explainability frameworks, and GenAI-powered narrative generation to translate forecasting outputs into actionable business intelligence for Amazon's business customers. The data scientist will build automated variance decomposition models and a causal model library with standardized pipelines, applying techniques from causal inference and time-series econometrics. | Post-trainData | 7 |
| Data Scientist II, Long Term Planning and Forecasting This Data Scientist II role focuses on building scientific tooling for how business customers interact with Long-Term Planning and Forecasting (LTPF) forecasts and plans. The role involves developing causal inference models, automated explainability frameworks, and variance bridging methodologies. It also includes building GenAI-powered narrative generation capabilities and automated hypothesis ranking to synthesize quantitative variance outputs into human-readable performance summaries and identify drivers of forecast error. The position emphasizes leading cross-functional programs, defining multi-year strategy, and leveraging insights for strategic decision-making. | Post-trainData | 7 |
| Economist II, GMAC Economics Economist II role focused on causal inference and machine learning for Prime Video Ads, involving experiment design, model building, and translating findings into business decisions. Requires a quantitative approach and end-to-end model implementation. | Post-train | 7 |
| Applied Scientist, Shopping Convo Foundations - Pre-purchases Science Research and develop novel ML approaches for catalogue expansion and product attribute challenges, translating scientific breakthroughs into production-ready solutions at Amazon scale. | Post-train | 7 |
| Applied Scientist, Shopping Convo Foundations - Pre-purchases Science Research and develop novel ML approaches for catalogue expansion and product attribute challenges, translating scientific breakthroughs into production-ready solutions at Amazon scale. | Post-train | 7 |
| Senior Applied Scientist, Shopping Convo Foundations - Pre-purchases Science Senior Applied Scientist role focused on research and development of novel ML models for Amazon's shopping catalogue expansion and product attribute challenges, aiming for high precision and production-ready solutions. | Post-train | 7 |
| Data Science - Forecasting & Lab, SCOT Forecasting & Lab This role focuses on improving existing machine learning methodologies within Amazon's supply chain optimization technologies. Responsibilities include analyzing large datasets, developing new data sources, enhancing and testing models, running computational experiments, and fine-tuning model parameters. The role also involves formalizing model assumptions, identifying outliers, and communicating findings to various stakeholders. Collaboration with internal and external researchers, including publishing papers, is expected. | Post-train | 7 |
| Data Scientist, SCOT Forecasting and Labs - CIV Team Data Scientist role focused on developing and implementing statistical, causal, and machine learning techniques for forecasting and inventory management within Amazon's retail supply chain. The role involves creating prototypes, collaborating with software teams for production implementation, and analyzing key business metrics to influence business direction. | Post-train | 7 |
| Senior Computational Biologist, Special Projects Senior Computational Biologist role focused on developing advanced computational methods and predictive models for complex, multi-modal datasets in the healthcare space. The role involves building interpretable models, integrating diverse data sources, and uncovering actionable insights, operating within an entrepreneurial and rapidly evolving environment. | Post-train | 7 |
| Data Scientist II, PV APAC and ANZ Analytics Team The Data Scientist II role at Amazon Prime Video focuses on analyzing customer viewing data to provide business insights and optimize content selection. The role involves developing and deploying new ML models using various data types to understand and predict customer behavior, supporting business reporting, and translating insights into actionable recommendations. The position requires strong data science, ML, and statistical skills, with experience in SQL, Python, and ML modeling techniques. The candidate will work with large datasets and collaborate with research scientists and economists to improve optimization across tools. | Post-train | 7 |
| Sr. Design Technologist, Prime Video - AI Content Generation 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. | Post-train | 7 |
| Business Research Analyst - II, RBS This role focuses on implementing and building ML/LLM solutions for business needs, collaborating with scientists, writing code, and optimizing solutions. It involves product pilots and developing technical documentation. | Post-train | 7 |
| Sr Applied Scientist, Sponsored Products and Brands Ads Response Prediction This role focuses on developing and deploying machine learning models for Amazon's Sponsored Products and Brands Ads, aiming to improve customer experience and advertiser effectiveness. The scientist will conduct data analysis, build and optimize ML models, run A/B experiments, and collaborate with engineers to productionize solutions. They will also research new ML modeling techniques to enhance business outcomes. | Post-train | 7 |
| Applied Scientist, Prime Video - Content Localization, Understanding & Enrichment Applied Scientist role at Amazon Prime Video focusing on content localization, understanding, and enrichment using NLP and computer vision. The role involves leading research direction, developing deep learning algorithms, and potentially building agentic systems for content understanding. | Post-trainAgent | 7 |
| Applied Science Manager , Stores Foundation AI (SFAI) Manager for a team working on LLM and/or VLM post-training and alignment for new personalized shopping experiences, leveraging customer behavioral data. | Post-trainAgent | 7 |
| Applied Scientist III - AMZ9674037 Applied Scientist III role at Amazon Web Services focusing on the design, development, evaluation, and deployment of data-driven models and analytical solutions for ML and NL applications. Responsibilities include applying statistical modeling, optimization, and ML techniques, building and deploying models in production, and researching novel ML approaches. Requires a Master's degree in a related field and experience in programming and developing supervised/unsupervised ML models. | Post-train | 7 |
| Language Data Scientist, Alexa AI The Language Data Scientist role on the Alexa AI team focuses on analyzing and evaluating speech and interaction data to improve machine learning models and customer experience. This role involves leading dialog evaluation, developing annotation workflows, conducting research studies on speech and customer-Alexa interactions, and defining customer experience metrics. | Post-trainEval Gate | 7 |
| Applied Scientist, Prime Video - Content Reasoning, Enrichment and Localization Team 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. | Post-trainData | 7 |
| Sr AI Editorial Lead (Portuguese), AI Shopping, International This role focuses on curating and evaluating content to train and optimize AI models for conversational shopping experiences in new marketplaces and languages. It involves defining guidelines, ensuring response quality, analyzing errors, and creating frameworks for prompt tuning and management. The role also guides the development of automation and internal tools for editorial curation and evaluation, collaborating with product, science, and engineering teams. | Post-trainData | 7 |
| Applied Scientist, Special Projects 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. | Post-train | 7 |