Software Development Engineer role at Amazon Pharmacy focusing on building ML-driven supply chain systems. Responsibilities include system design, development, operational ownership, and collaboration, with an emphasis on productionizing ML models for demand forecasting, procurement, and inventory placement. The role involves working with large-scale datasets, distributed systems, and operations research techniques within a regulated healthcare environment.

Software Development Engineer II role focused on building AI-powered learning solutions and content creation tools using generative AI and an agentic AI framework for Amazon's talent development ecosystem.

Software Development Engineer III role focused on building and owning end-to-end large-scale distributed systems and AI/ML-powered applications for Amazon's product catalog. The role involves designing, implementing, and operating systems for product identity, matching, and relationship management, leveraging AI/ML solutions including multimodal LLMs, embedding-based systems, and agentic systems. Key responsibilities include leading architecture decisions, building and optimizing inference infrastructure, and partnering with Applied Scientists to productionize ML research.

Software Development Engineer role focused on building and improving automated, algorithmic solutions using machine learning, computer vision, and robotics to prevent, detect, and correct inventory issues in Amazon's fulfillment centers. The role involves building new software services and tools, designing production systems, and working with research scientists on next-generation intelligent systems.

This role is for a Data and AI Cloud Architect on the AWS Professional Services team in Taiwan, focusing on the manufacturing and semiconductor industries. The architect will design and implement modern data platforms, analytics solutions, and AI/ML workloads on AWS, acting as a trusted technical advisor to enterprise customers. Key responsibilities include leading architecture design, building end-to-end data architectures, architecting AI/ML solutions using AWS services like SageMaker and Bedrock for industry-specific use cases, collaborating with stakeholders on data strategies, mentoring junior consultants, and developing reusable assets. The role also involves partnering with AWS teams, contributing to thought leadership, and staying current with data engineering, analytics, and generative AI trends. Basic qualifications include experience conveying technical concepts, a relevant degree or equivalent experience, 8+ years in data/cloud architecture with 5+ years on AWS, deep expertise in data platform technologies (Python, SQL, Spark, Scala), and fluency in Mandarin and English. Preferred qualifications include experience with large-scale transformation programs, domain expertise in manufacturing/semiconductor industries, knowledge of Industry 4.0, experience with generative AI architectures (RAG, fine-tuning, agents), and familiarity with Taiwan's data privacy regulations.

ML Software Engineer focused on the inference data plane, optimizing software for custom hardware to run large models efficiently. Responsibilities include kernel optimization, model architecture integration, serving framework integration, and performance profiling for LLM inference.

Product Manager for AWS FinOps Agent, focusing on building agentic workflows and defining the strategy for generative AI in cloud financial management. The role involves understanding customer needs, defining product vision, and collaborating with engineering and applied science teams to deliver autonomous FinOps experiences.

Senior Software Development Engineer role focused on building the intelligence layer for Amazon Robotics manipulation workcells. This involves designing, building, and operating distributed systems for work selection, data processing, ML lifecycle management, and predictive modeling. The role operates across the full ML and data lifecycle, impacting millions of packages and directly influencing fulfillment cost.

This role focuses on building the next generation of software verification tools by combining advances in AI, cloud computing, and formal verification techniques. The Principal Applied Scientist will define roadmaps, lead delivery of AI solutions, identify and implement new analysis capabilities, and explore generative AI for tasks like requirement formalization, test generation, and proof repair. The role involves using a combination of traditional formal methods and generative AI to solve complex code analysis problems.

Software Development Engineer role at Amazon Prime Video focusing on personalization and Computer Vision/Machine Learning to enhance customer viewing experiences. The role involves owning architecture, designing and building scalable solutions, and tackling complex technical challenges from data pipelines to large-scale services, with a focus on deploying ML models in production.

Software Development Engineer role focused on building AI/ML-powered products and infrastructure for data integration workflows within Amazon's AWS Utility Computing organization. The role involves designing, developing, and optimizing AI/ML systems, collaborating with data scientists, and contributing to the full software development lifecycle.

Software Development Engineer role focused on building AI/ML-powered products and infrastructure for data integration workflows within Amazon's AWS Utility Computing organization. The role involves designing, developing, and optimizing AI/ML systems, collaborating with data scientists, and contributing to the full software development lifecycle.

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.

This role focuses on designing, implementing, and deploying GenAI and ML applications and models on AWS for customers. It involves providing technical guidance, gathering requirements, and advising on model training and deployment strategies, with a strong emphasis on AWS AI/ML services.

Software Development Engineer for Amazon Search Autocomplete and Navigation AI. This role focuses on building next-generation mission understanding models and data collection frameworks, integrating models into large-scale, real-time production systems, and analyzing data to optimize system design and model performance. The position involves developing scalable data pipelines, designing and executing experiments, and managing ML initiatives.

Senior Product Manager for Alexa Canada, focusing on expanding Alexa's presence in the Canadian market. This role involves defining user needs, creating product roadmaps, understanding market dynamics (including emerging AI/ML), developing requirements, leading cross-functional teams, owning the customer experience, tracking launches, managing trade-offs, monitoring performance, and working closely with engineering. The role requires technical depth to evaluate AI model behavior and technical approaches, and a proactive exploration of new AI capabilities like large language models and agentic AI.

Research and develop new AI technologies for personalization using recommendations, information retrieval, and large language models. Build large-scale ML solutions for customer experiences.

Principal Product Manager, Technical for Amazon Music's Agent Experience and Music Intelligence. This role defines the strategic vision for AI-powered music experiences across all Amazon Music product surfaces, focusing on cross-platform strategy, intelligence layer utilization, and emerging technologies like generative AI. The PM will influence senior leadership, partner across organizations, and translate complex technical capabilities into customer-facing product strategies with clear business cases.

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.

Senior Machine Learning Engineer responsible for building and owning real-time ML serving systems for ad selection in Sponsored Products and Brands at Amazon. The role involves driving technical direction, designing scalable pipelines, optimizing model performance, and mentoring engineers, operating at massive scale with strict latency SLAs. It touches on deep learning, NLP, LLMs, and distributed systems, impacting shopper experience and advertiser ROI.

Senior AI Solutions Architect for AWS, focusing on guiding enterprise customers in adopting and scaling GenAI/ML and Agentic technologies. The role involves building technical relationships, designing scalable architectures, providing technical leadership, and creating content like whitepapers and workshops. It requires hands-on experience with AWS AI services, implementing solutions including RAG, fine-tuning, inference, and agentic workflows, and a strong understanding of production AI systems.

Senior Applied Scientist focused on transforming research into scalable, real-world solutions for Workplace Health & Safety, leading end-to-end design, development, and deployment of large-scale scientific systems, and mentoring junior scientists.

Customer Engineer focused on building Agentic AI and multi-modal Generative AI applications and workflows for financial services customers on AWS. This role involves creating end-to-end solutions, prototypes, and modern data applications, with a strong emphasis on hands-on development with AWS AI services.

Software Development Engineer role focused on building AI/ML-powered products and infrastructure for data integration workflows at Amazon. The role involves designing, developing, and optimizing systems, collaborating with data scientists, and contributing to the full software development lifecycle. Requires experience with ML/LLM fundamentals and optimization of model execution.

Sr. Technical Program Manager to drive the delivery of AI-powered production capabilities for Prime Video and Amazon MGM Studios. The role involves managing end-to-end delivery across Engineering, Product, Applied Science, UX, and creative production teams, translating production requirements into technical execution plans, managing dependencies, and ensuring delivery against ambitious milestones for an AI-native production platform called Nara.

Software Development Engineer focused on building the compiler infrastructure and software stack for custom neural accelerator silicon designed for edge AI capabilities. The role involves optimizing deep learning workloads, model quantization, and compression for efficient execution on hardware with limited memory, ultimately enabling large AI models to run on edge devices.

Principal Product Manager - Tech for Sponsored Products and Brands, focusing on advertiser-facing Gen AI products and conversational commerce. The role involves defining product vision, rethinking campaign management using LLMs, and collaborating with various teams to deliver intelligent, adaptive experiences. It requires deep Ad Tech expertise and the ability to influence across organizational boundaries.

This role focuses on developing and implementing Control Barrier Function (CBF) algorithms for Amazon's robot fleet, ensuring safety and reliability in real-world conditions. The scientist will bridge the gap between theoretical mathematics and practical hardware implementation, addressing challenges like sensor noise and computational budgets, with the goal of achieving third-party safety certification.

This role focuses on building and delivering Generative AI solutions for customer-facing business problems using AWS services and open-source technology. Responsibilities include designing, developing, and evaluating solutions like RAG, multi-agent systems, and model fine-tuning, as well as providing guidance and creating best practices for customers. The role also involves analyzing data to optimize processes and identify investment opportunities.

Software Development Engineer II role focused on building the backend services for an AI-powered conversational agent (Amazon Marketing Cloud Assistant) that allows advertisers to interact with data using natural language. The role involves designing and building scalable data pipelines, LLM orchestration, prompt engineering, tool use, agent workflows, and contributing to the evaluation framework for agent accuracy. It operates at the intersection of LLMs, distributed systems, and large-scale advertising data.

This role is for a Sr. AI Solution Architect at AWS, focusing on helping customers adopt and scale GenAI/ML and Agentic technologies. The architect will build technical relationships, design 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 contributing reusable assets. The role requires hands-on experience with AWS AI services, implementing RAG, fine-tuning LLMs, deployment, distributed inference, and MLOps.

Software Development Engineer II (SDE II) for Amazon India Ads, focusing on building scalable, low-latency AI/ML solutions for digital advertising. The role involves designing and implementing ML infrastructure for recommendations, ads ranking, personalization, and search, integrating generative AI and LLMs. Responsibilities include working with modern AI/ML technologies, driving technology choices, contributing to technical direction, coding and supporting distributed systems, implementing AI-powered products, and owning product operations with a focus on responsible AI.

Research Engineer role focused on building experiment frameworks, infrastructure, and deployment packages for Generative AI models within Prime Video. Responsibilities include managing GPU clusters, containerizing models, and developing monitoring pipelines for production deployment. The role supports applied scientists and involves end-to-end ownership of model training and deployment.

This role focuses on designing, implementing, and managing GenAI and ML solutions on AWS for customers. The consultant will provide technical guidance, collaborate on requirements, and advise on industry trends, ultimately helping customers achieve their business outcomes through AWS AI/ML services. The role involves working with customers to build and deploy models, with a focus on the end-to-end solution.

This role focuses on designing, implementing, and managing GenAI and ML solutions on AWS for customers. The consultant will provide technical guidance, collaborate with stakeholders on model training and deployment strategies, and act as a trusted advisor on emerging technologies. The role emphasizes using AWS AI/ML services and involves working with customers to achieve their business outcomes.

This role focuses on designing, implementing, and managing GenAI and ML applications and models on AWS for customers, acting as a trusted advisor and providing technical guidance throughout the project lifecycle. It involves understanding customer needs, proposing solutions, and ensuring successful deployment and optimization of AI/ML services.

This role focuses on designing, implementing, and delivering GenAI and ML applications for enterprise customers on AWS. The consultant will act as a trusted advisor, providing technical guidance and collaborating with stakeholders to build custom AI tools and solutions, with a strong emphasis on customer success and project delivery.

Software Development Engineer II (SDE II) for Amazon Robotics Scanless Tech team, focusing on developing and deploying machine learning and computer vision based software technologies for robotics applications. The role involves building edge and cloud CV applications, leveraging AWS ML, optimizing fulfillment infrastructure, and partnering with Applied Scientists to develop ML applications. The team's solutions are core to the business and deployed at scale.

This role focuses on validating next-generation machine learning accelerators for AWS, covering the entire vertical stack from silicon to system. The engineer will work on hardware and software validation, ensuring performance, accuracy, and reliability of ML accelerators used in AWS data centers. Responsibilities include developing validation strategies, executing test plans, debugging hardware and software issues, and collaborating with cross-functional teams.

Data Scientist I role focused on developing and delivering core data science capabilities for AI-enabled operations, leveraging LLMs, Generative AI, and predictive analytics to solve complex operational problems within Amazon's global footprint. The role involves assessing solution approaches, designing extensible solutions, owning end-to-end data science projects, collaborating with cross-functional teams, and contributing to AI strategy and investment priorities.

Applied Scientist II role focused on building and deploying generative AI technologies for Amazon's Sponsored Products and Brands advertising platform, with a focus on video content. The role involves developing new solutions, evaluating technologies, and mentoring other scientists, while working with LLMs and production environments.

Software Development Engineer role focused on building and operating agentic AI solutions for security monitoring of relational databases (Aurora and RDS) at massive scale. The role involves capturing and analyzing security telemetry to identify and mitigate threats, requiring strong distributed systems engineering skills and operational excellence.

This Applied Scientist role focuses on building and deploying AI/ML models and LLM-powered systems for Amazon's North America Stores. The role involves developing workflows that combine ML models with optimization engines and human-in-the-loop capabilities, building scalable data and inference pipelines, and designing experimentation frameworks. The goal is to automate complex business processes and serve real-time predictions in production, impacting areas like supply chain, customer engagement, and inventory management.

This role is for a Senior System Development Engineer focused on high-performance accelerator servers for AI/ML at AWS. The engineer will be responsible for designing, delivering, and operating next-generation infrastructure for AI training and inference, focusing on performance, efficiency, and scalability. The role involves deep technical understanding of the full stack from hardware to software, systems debugging, and leading complex projects.

Software Development Engineer II role in Amazon's FinTech group, focusing on building and deploying machine learning applications for transaction analysis, fraud detection, and financial process optimization. The role involves working with large datasets, collaborating with scientists and business teams, and applying ML techniques like forecasting, classification, and anomaly detection, including Generative AI and LLMs.

This role focuses on designing, implementing, and managing GenAI and ML solutions on AWS for customers. The consultant will provide technical guidance, collaborate with stakeholders on model training and deployment strategies, and act as a trusted advisor on emerging technologies. The role requires experience in hosting and deploying GenAI/ML solutions, including pre-processing, training, fine-tuning, and inference.

This role focuses on designing, implementing, and managing AWS GenAI/ML solutions for customers, providing technical guidance, and acting as a trusted advisor. It involves working with customers to understand their needs and proposing effective strategies for model training, building, and deployment, with a strong emphasis on using AWS AI/ML services.

Research Scientist role focused on building novel solutions for workforce optimization using operations research, causal inference, machine learning, and generative AI. The role involves designing simulation and optimization models for scheduling, hiring, and task assignment, developing causal inference frameworks, and collaborating with senior leaders to influence strategic decisions. The work directly impacts operational efficiency and employee experience at Amazon's global scale.