Amazon

Software Development Engineer to develop a multi-modal, multi-lingual web-scale information retrieval system that combines LLMs with retrieval systems for question-answering, knowledge synthesis, and information grounding. The role involves building data pipelines, optimizing core algorithms and ranking models, designing data structures and indexing techniques, optimizing performance and scalability, integrating ML models, and developing control plane systems for the IR system infrastructure. Experience with Rust, large-scale distributed systems, and ML integration is required.

Software Development Manager for Amazon Web Services (AWS) Elastic Block Store (EBS) Capacity Engineering team. The role involves leading a team to invent and build a new capacity forecasting and planning platform using AI/ML, including machine learning models, algorithms, and agents, to automate capacity planning and purchasing for AWS data centers globally. The focus is on optimizing fleet servers, predicting demand, and balancing service, infrastructure, financial, and business constraints to support the rapid growth of AWS, especially driven by AI workloads.

Software Development Engineer III role focused on building conversational ad experiences using generative AI and LLMs for Amazon Ads. The role involves designing and developing new features, integrating AI solutions, pioneering conversational AI approaches, and creating scalable, low-latency systems. It requires strong software engineering skills and collaboration with science teams to implement LLM models in production and contribute to LLMOps.

Software Development Engineer II at Amazon focused on building advanced robotics systems that integrate AI, control systems, and mechanical design for automation. The role involves developing a software framework for robot deployment, generalization, integration with large models and control techniques, and human-safe solutions. Key responsibilities include designing manipulation components, cloud/edge inferencing, real-time communication, and human-machine interfaces.

Software Development Engineer focused on real-time ad personalization and insights, leveraging generative AI technologies like latent diffusion models, LLMs, and RL to tailor visual ad experiences. The role involves investigating new technologies, building data pipelines, and developing platforms for ML model deployment in the Dynamic Creative Optimization (DCO) domain.

This role is for a PhD student intern focused on research science at Amazon. The intern will apply advanced statistical techniques and AI/ML technologies to solve complex problems, implement prototypes, and work with large datasets. Responsibilities include data collection, analysis, interpretation, developing and testing hypotheses, documenting findings, and collaborating with team members. The role emphasizes hands-on scientific work, data analysis, experimental design, and computational modeling.

This Applied Scientist Intern role at Audible focuses on developing innovative AI solutions for recommendation, content understanding, and AI-powered product experiences. The intern will design and implement ML models, frameworks, and evaluation methodologies, enabling self-service automation and building AI systems that drive internal productivity and new product features. The role emphasizes practical implementation, collaboration with cross-functional teams, and raising AI fluency across the organization.

This role focuses on building AI-powered prototype solutions, agents, and automations to improve marketer productivity within Amazon Ads. The AI Builder will work with stakeholders to identify pain points, develop AI-native workflows, and ship AI use cases from pilot to production, establishing reusable frameworks and setting standards for AI transformation in marketing.

Data Scientist II role focused on developing and supporting data science methodologies and models for Amazon's global inventory management and buying programs. The role involves deriving causal inferences, modeling variations, and building tools to drive key decisions in buying and sourcing strategies, with a focus on massive datasets and operational efficiency.

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.

Principal Product Manager, Technical for Amazon's Shopper Understanding and Response Prediction team. This role focuses on driving business growth by defining and executing strategies for personalized shopping experiences on Amazon Search and Product pages. It involves working with deep learning models, large-scale ML pipelines, and real-time serving infrastructure, leveraging GenAI to improve shopper understanding and prediction systems. The role requires close collaboration with engineers and applied scientists to deliver tailored shopping experiences and requires strategic vision, technical depth, and analytical rigor.

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.

This role focuses on developing advanced robotics systems that integrate AI, control systems, and mechanical design for automation. The scientist will design and implement whole-body control methods for balance, locomotion, and dexterous manipulation, utilizing state-of-the-art learned and model-based control methods, including imitation learning and reinforcement learning. The goal is to create robust, safe, real-time controllers for robots operating in dynamic environments and alongside humans.

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.

PhD student internship focused on Automated Reasoning for cloud computing, involving research into novel approaches, development of solutions, and deployment into production. Expertise sought in theorem proving, SAT/SMT solvers, program analysis, and synthesis, with a potential link to ML/LLMs.

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.

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 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.

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.

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.