Amazon

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 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 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.

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.

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 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 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.

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.

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.

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.

This role focuses on converting AI ambition into programs that can be delivered, operated, and scaled in production environments, acting as a trusted advisor to customers on adopting GenAI/ML and Agentic technologies. The Senior AI Solution Architect will manage technical relationships, make recommendations on architecture, and influence roadmap enhancements. Responsibilities include building technical relationships, advising on security, cost, performance, and operational efficiency for GenAI/ML and Agentic projects, and acting as the voice of the customer internally. The role involves defining cloud-native GenAI/ML and Agentic architectural patterns, creating and sharing best practices, technical content, and reference architectures, and evangelizing AWS technology for GenAI/ML and Agentic workloads through various channels. Additionally, it requires leading hands-on deep dives and technical workshops, contributing reusable code and assets.

Senior AI Solution Architect for AWS, focusing on guiding customers in adopting GenAI/ML and Agentic technologies. This role involves building technical relationships, recommending architectures for GenAI/ML and Agentic projects, influencing roadmaps, defining cloud-native architectural patterns, and creating technical content. The role requires hands-on experience with AWS AI services, LLM integration, fine-tuning, inference, RAG, evaluation, vector databases, agentic workflows, and MLOps.

This role focuses on converting AI ambition into programs that can be delivered, operated, and scaled in production environments. 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.

This role is for a Senior AI Specialist Solutions Architect at AWS, focusing on helping enterprise customers adopt and scale GenAI/ML and Agentic technologies. The role involves building technical relationships, designing scalable architectures, advising on best practices, and contributing to the development of AWS AI services. It requires hands-on experience with AWS AI services, implementing solutions like RAG, LLMs, and agentic workflows, and translating customer needs into technical solutions.

This role is for a Senior AI Solutions Architect at AWS, focusing on helping customers adopt and scale Generative AI, ML, and Agentic technologies. The architect will build technical relationships, provide architectural guidance, and translate customer needs into scalable solutions on AWS. Responsibilities include advising on security, cost, performance, and operational efficiency, contributing to AWS service roadmaps, and creating technical content like whitepapers and workshops. The role requires hands-on experience with AWS AI services, implementing RAG, fine-tuning LLMs, and deploying LLMs.

This role is for a Senior AI Solutions Architect at AWS, focusing on helping customers adopt and scale GenAI, ML, and Agentic technologies. The architect will build technical relationships, craft scalable architectures, provide recommendations on various aspects of cloud adoption, and act as the voice of the customer internally. Responsibilities include creating technical content, leading deep dives, and ensuring solutions are production-ready. The role requires hands-on experience with AWS AI services, implementing RAG, fine-tuning LLMs, and MLOps.

This role focuses on converting AI ambition into programs that can be delivered, operated, and scaled in production environments. 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 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.