Amazon

Data Engineer role focused on building and operating data pipelines, models, and platform infrastructure for Ring's analytics, science, and AI initiatives. The role involves designing end-to-end data lifecycles and building multi-agent solutions to automate data engineering tasks. It also includes contributing to the shared data platform and AI/ML models.

Senior Software Development Engineer to lead architecture and design of AI data pipelines and large-scale distributed systems for Amazon Bedrock Knowledge Bases, a RAG service for enterprise data integration with FMs and agents. Focus on scaling services, innovating on Gen AI, and ensuring extensible, performant, and secure solutions.

Senior Software Development Engineer for Prime Video's Machine Learning Platform team, focusing on recommendation systems and ML infrastructure. The role involves end-to-end ownership of product, user experience, design, and technology to deliver state-of-the-art entertainment experiences. Responsibilities include designing and building ML infrastructure, tackling complex problems, delivering scalable ML platform solutions, writing code, mentoring engineers, and influencing technical strategy.

Software Development Engineer on the EC2 Nitro Machine Learning Systems team, focusing on building and optimizing performance measurement infrastructure for AI/ML workloads. The role involves establishing best-known configurations, translating performance insights into technical requirements, and analyzing training/inference performance across accelerated platforms. It requires expertise in low-level systems, ML frameworks, and serving layers.

Senior Software Development Engineer role focused on building and scaling EC2 compute platforms for machine learning workloads, including training and inference for LLMs and multimodal systems. The role involves designing innovative technologies, leading technical projects, developing regression testing systems, and collaborating with hardware teams to optimize platform designs for ML performance.

Applied Science Manager leading a team focused on optimizing drone fleet mission planning and orchestration using ML/RL and geospatial data to maximize deliveries per hour. The role involves path planning, scheduling, system architecture, and cross-functional collaboration, with a focus on turning research into deployed features.

Senior Software Development Engineer role focused on building and scaling machine learning infrastructure for EC2 Nitro, supporting training and inference workloads for various ML applications including LLMs and multimodal systems. The role involves designing innovative technologies, leading technical projects, developing regression testing systems, and collaborating with hardware teams to optimize platform designs for ML performance.

Senior Software Development Engineer to lead design and implementation of distributed AI data pipelines and large-scale distributed systems for Amazon Bedrock Knowledge Bases, a RAG service. Focus on technical leadership, architecture, and balancing execution with long-term needs.

Applied Scientist II role focused on enhancing ML accelerator software (Trainium/Inferentia) to accelerate customer adoption. Responsibilities include developing ML/RL for code generation/optimization, creating ML compiler techniques, building validation tools, and designing high-performance kernels. The role involves working with customers, engineering teams, and research communities to advance ML systems, with a focus on inference performance and training cost optimization.

Software Development Manager for Amazon Ads' Sponsored Products and Brands team, focusing on leveraging generative AI and ML to revolutionize advertising experiences. The role involves managing engineers, developing roadmaps for ML/GenAI solutions in ad retrieval, fostering cross-team collaboration, and hiring/developing talent. The team operates full-stack, from backend services to shopper-facing experiences, aiming to deliver personalized and context-aware advertising.

Software Development Engineer III role focused on leading the technical direction for autonomous navigation stack components, including task planning, motion planning, and control for production robotics systems. The role involves architecting and implementing ML/AI-based systems, impacting thousands of robots, and working with state-of-the-art technologies in a scaling environment.

This role focuses on applying machine learning to video processing, understanding, and content monetization within AWS Elemental. The scientist will prototype, optimize, and deploy advanced models into production, collaborate with cross-functional teams, and develop scalable solutions. The role also involves mentoring, contributing to operational tooling, and potentially publishing applied research. The primary focus is on shipping AI-powered features and enhancements for video services.

Sr. Applied Scientist at Amazon Prime Video focused on building and deploying sophisticated machine learning systems for content presentation and discovery. The role involves developing multi-modal embeddings, contextualized ranking systems, and reinforcement learning frameworks, with a strong emphasis on bridging science and engineering for production-scale deployment. Responsibilities include leading cross-functional science initiatives, mentoring junior talent, and working with large-scale data to create personalized customer experiences.

Machine Learning Engineer role focused on designing, implementing, and scaling Generative AI solutions for enterprise customers on AWS. The role involves working directly with customers to understand their needs, select and fine-tune models, develop proof-of-concepts, and provide technical guidance throughout the project lifecycle. It emphasizes customer success and driving AI transformation.

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.

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 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.

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 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.

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.

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.

The Sponsored Products and Brands team at Amazon Ads is seeking an Applied Scientist to leverage generative AI and machine learning to revolutionize advertising experiences. This role involves driving end-to-end ML projects, analyzing large datasets, building and deploying models into production, and establishing scalable processes for ML development and serving. The focus is on creating innovative ad tech and shopping experiences off the store, working with external and internal partners to connect systems, understand customers, and drive results at scale, with a GenAI-first approach.

Senior Applied Scientist role focused on developing and launching AI solutions for Amazon's Sponsored Products and Brands advertising business. This involves building recommendation systems leveraging generative models, designing and implementing end-to-end AI solutions, and defining a long-term science vision. The role requires experience in building ML models, deep learning, and working with large-scale distributed systems.

Senior Software Engineer role focused on driving technical strategy and architecture for robotic software systems, including perception, navigation, motor control, reasoning, and human-robot interaction. The role involves end-to-end delivery of complex systems, leading collaboration across research and ML teams, defining technical roadmaps, and developing production-level SDKs. The team is building robots for everyday life, aiming to make robotics development more accessible and intuitive.

Manager for an AWS Applied AI Solutions team focused on building foundational systems and consumer-facing features for trustworthy AI experiences at scale within the supply chain domain. The role involves leading engineering teams, driving technical strategy for privacy-preserving and responsible AI, and developing enterprise-grade AI applications.

Security Engineer focused on threat detection using ML and generative AI to build and improve detection capabilities at scale for Amazon's network.

Applied Science Manager to lead a team building and scaling a prompt generation pipeline for a conversational ad format powered by LLMs. The role involves developing prompt themes, quality frameworks, and driving coverage expansion, with a focus on personalization and experimentation to improve key metrics. Requires strong technical depth in NLP, LLMs, and information retrieval, along with management experience and the ability to influence product strategy.

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.