Amazon

This role focuses on designing, developing, and maintaining data infrastructure and ETL pipelines to support business intelligence initiatives, with a specific emphasis on implementing AI/LLM-powered solutions for task automation and statistical analysis for business decision-making. The role involves collaborating with cross-functional teams to build AI-ready foundational capabilities within the Global Selling organization.

This role is for an Associate II, ML Data Operations at Amazon Robotics, focusing on human-in-the-loop data annotation for training and validating machine learning models. It's a non-technical role that involves precise annotation of text, video, and image data, identifying operational friction, and ensuring data quality for LLM capabilities. The role supports the development of robotics and fulfillment technologies.

Senior Applied Scientist to work on AI and program analysis for a deep learning compiler stack, optimizing models for ML accelerators (Inferentia, Trainium). Role involves designing, developing, and deploying analyzers for ML compiler stages, architecting business-critical tooling, publishing research, and mentoring. Focus is on compiler technology and deep-learning systems software, with a preference for ML/AI accelerator background.

Software Development Engineer II role focused on building and improving personalization and recommendation features for Amazon's consumer platform, leveraging machine learning and big data technologies.

This role focuses on using advanced data analysis, including Machine Learning and AI tools, to identify and prevent fraud and abuse across Amazon's e-commerce platforms. The specialist will manage critical projects, scale findings through technology and analytics, and develop systematic solutions to endemic problems. A key responsibility includes utilizing agentic AI systems to automate workflows and accelerate investigations.

Senior Software Development Engineer role focused on designing and developing highly scalable distributed systems for Amazon's Sponsored Products and Brands advertising platform. The role involves integrating Generative AI solutions, collaborating with data scientists on machine learning experiments, and implementing end-to-end solutions to improve predictive models and infrastructure within the e-commerce advertising domain.

Software Development Engineer on the Amazon OpenSearch Service team, focusing on building and scaling distributed systems for search and observability. The role involves designing, developing, and deploying reliable services, working with languages like Rust, Java, and Python, and tackling challenges in cluster management, data ingestion, and query optimization. The team is described as AI-led and working on greenfield opportunities.

Software Development Engineer responsible for developing and maintaining high-performance runtime libraries and drivers for AWS ML accelerators (Inferentia and Trainium). The role involves managing the full development lifecycle of the Neuron Runtime, optimizing AI workloads, improving ML kernels and frameworks, and supporting multiple ML frameworks. Requires experience in distributed systems, AWS services, and end-to-end service ownership.

This role focuses on identifying and disrupting sophisticated tax fraud schemes within Amazon's marketplace. The specialist will own fraud investigations, extract generalizable patterns for automation, and collaborate with Science, Product, and Tax teams to improve prevention and detection systems. The role involves analyzing investigations to identify technical controls, data signals, and model features for early detection, and leading incident response for high-impact fraud events.

This role focuses on preparing training data for ML algorithms using cloud infrastructure, performing architecture feasibility analysis, and evaluating video picture quality using industry tools and standards. The primary deliverable is the prepared training data for ML models.

This is an internship role for a Software Development Engineer at Amazon in Canada. The intern will work on designing, building, and operating innovative products and services, leveraging cloud-native architectures and microservices. A key responsibility includes leveraging and contributing to GenAI and AI-powered tools to enhance development productivity. The role requires experience with programming languages, data structures, and algorithms, and is for students pursuing a STEM degree with a conferral date after the internship.

Software Development Manager for AWS Compliance & Security Assurance, focusing on Denied Party Screening. The role involves leading teams to build and scale ML/LLM-powered detection and resolution systems to prevent prohibited transactions with denied entities, handling significant daily event volumes and scaling challenges. The manager will define team vision, shape technical strategy, mentor engineers, and ensure operational excellence for these AI/ML systems.

This role focuses on building and operating AWS cloud offerings that enable high performance and scalability in AI/ML and HPC workloads, specifically designing and delivering server hardware for AI training and inference. The candidate will work across the full technical stack from baremetal hardware to userland software, solving complex architectural problems related to server systems, their testability, reliability, and diagnosis, with the goal of delivering continuous price-performance improvements for large language models at cloud scale.

Software Development Engineer II on the DynamoDB Capacity and Customer Entitlement team, responsible for designing and building production systems that optimize capacity planning and fleet scaling for DynamoDB's infrastructure. This role involves developing automated scaling algorithms, capacity management tools, and operational workflows, including building ML-integrated prediction systems for demand forecasting and capacity allocation.

This role focuses on identifying opportunities to integrate AI/ML and automation into seller support workflows within Amazon Business. The Program Manager will lead initiatives to improve seller experience and operational efficiency by designing, piloting, and scaling AI solutions, with a focus on reducing manual effort and speeding up issue resolution. While not directly building models, the role is critical in driving the application and adoption of AI technologies to solve business problems.

Software Engineer role within AWS Professional Services focused on delivering cloud-native solutions using AWS services, with a specific emphasis on leveraging AI/ML services to build AI-enabled applications and agent architectures for customers.

Software Development Engineer role at Amazon Web Services (AWS) focusing on building and maintaining code, implementing software solutions, and collaborating with cross-functional teams. The role also mentions potential specialization in Artificial Intelligence/Machine Learning and Healthcare AI, with preferred qualifications in ML frameworks and fundamentals.

This role builds the foundational data platform for robotics and ML development, focusing on data pipelines, storage, and transformation to support ML training and fleet monitoring.

This role is for a Principal Technical Program Manager at Amazon, focusing on brand measurement solutions within Ad Tech and Data Science. The role involves leading the development and delivery of innovative solutions that help advertisers measure, analyze, and optimize their brand-building campaigns. It requires managing large-scale technical programs at the intersection of advertising technology, machine learning, and distributed systems, and delivering AI-driven insights to empower advertisers. The position emphasizes program management, technical strategy, cross-functional leadership, and operational excellence in a mature, large-scale environment.

Software Development Engineer II role within AWS Applied AI Solutions, focusing on building new and contributing to existing healthcare AI services like HealthLake, Comprehend Medical, and HealthScribe. The role involves designing, developing, and testing scalable software systems for cloud-based healthcare applications, collaborating with cross-functional teams, and ensuring operational excellence and compliance.

This role focuses on applying professional services advisory skills to Amazon's internal governance, risk management, and assurance (GRA) capabilities. The primary goal is to develop and embed best practices, drive business change through tailored functional insight, and lead the scoping, design, and execution of automation within GRA, with a specific focus on AI and machine learning models. The role involves advising partners on risk reduction, creating data-driven narratives for senior leadership, and ensuring the effectiveness of internal controls. While the role advises on AI/ML models, it does not appear to involve direct development or shipping of these models.

Lead Engineer for Amazon's Trainium Manufacturing Quality & Reliability organization, focusing on bridging manufacturing outcomes with datacenter operational performance. This role involves establishing and operating a preparedness lab to analyze datacenter performance of manufactured systems, identify root causes of field issues, and feed insights back into manufacturing processes, test strategies, and design improvements. The position also influences hardware design for DFM, DFR, and DFT, establishes data-driven analytics frameworks connecting manufacturing test data to datacenter performance (leveraging ML), and develops manufacturing processes at ODMs/CMs. The role requires experience with AI/ML acceleration systems and managing cross-functional teams.

This role focuses on evaluating AI systems, specifically LLMs, by designing and executing benchmarking and audit activities. It involves assessing model quality, compliance, robustness, and fairness, as well as handling annotations for training and measuring AI models. The role also includes preparing audit reports and ensuring data quality.

This role is for a Senior Solutions Architect focused on AWS security services, helping enterprise customers adopt and operationalize these services, particularly in the context of securing generative AI and agentic architectures. The role involves owning the technical relationship, architecting solutions, and providing feedback to product teams. While it touches on AI/agentic architectures, the core function is security service adoption and operationalization, not building AI models or systems themselves.

This role focuses on designing and implementing intelligent automation solutions for financial operations using AI, ML, LLMs, and RPA tools. The engineer will optimize existing automations, gather requirements, lead projects, and ensure reliability and integration across systems.

Senior Software Engineer focused on DevOps for AWS's custom ML chips (Trainium/Inferentia), enabling rapid software development for AI training and inference. The role owns CI/CD pipelines, release processes, and hardware-in-the-loop testing infrastructure to ensure timely and quality software delivery for silicon development.

Solutions Architect for AWS Enterprise customers, focusing on designing and building cloud solutions, including AI-driven ones. The role involves acting as a technical advisor, translating requirements into solutions, and building prototypes. Experience with AI/ML solutions, Generative AI, and Agentic applications is preferred.

Senior Treasury Analyst role focused on treasury operations and banking relationships to support global expansion and implementation projects. The role involves managing cash operations, developing banking relationships, leading implementation projects, and leveraging Generative AI tools for automation and scalability.

This role focuses on developer advocacy, guiding developers on how AI is changing software development, adopting AI-powered tools, and building on AWS. The advocate will create technical content, build community, and provide feedback to product teams.

Design and implement scalable and reliable approaches to support or automate decision making throughout the business. Apply a range of data science techniques and tools combined with subject matter expertise to solve difficult business problems and cases in which the solution approach is unclear. Acquire data by building the necessary SQL / ETL queries. Import processes through various company specific interfaces for accessing Oracle, RedShift, and Spark storage systems. Build relationships with stakeholders and counterparts. Analyze data for trends and input validity by inspecting univariate distributions, exploring bivariate relationships, constructing appropriate transformations, and tracking down the source and meaning of anomalies. Build models using statistical modeling, mathematical modeling, econometric modeling, network modeling, social network modeling, natural language processing, machine learning algorithms, genetic algorithms, and neural networks. Validate models against alternative approaches, expected and observed outcome, and other business defined key performance indicators. Implement models that comply with evaluations of the computational demands, accuracy, and reliability of the relevant ETL processes at various stages of production.

The Catalog Specialist will support Machine Learning (ML) models and data science classification algorithm development by performing data annotation and labeling for ML model training and evaluation. This role collaborates with product, technology, and science teams to ensure high-quality annotated data and improve annotation processes.

Senior Technical Program Manager to define, own, and drive technical programs for GenAI/Agentic AI solutions within AWS Applied AI Solutions, focusing on supply chain operations. The role involves partnering with product management and technical leadership to identify opportunities, influence strategy, and align roadmaps across engineering and science teams.

Software Development Engineer role focused on building edge compute solutions for industrial automation within Amazon's fulfillment network. The role involves working across the full software development cycle, from low-level machine controls to cloud-based solutions, and developing infrastructure for warehouse automation systems. While the team works alongside AI/ML teams and the role touches on AI/ML solutions, the core responsibility is in engineering the automation and edge compute infrastructure.

This role focuses on developing and building new ML and statistical forecasting models for Amazon Stores' financials, aiming to improve financial decision-making and planning for senior leadership. It involves working with stakeholders, collaborating with various teams for production implementation, and adapting new modeling techniques.

This role supports Machine Learning (ML) models and classification algorithm development by performing data annotation and ensuring high-quality standards for annotated data. The specialist collaborates with product, technology, and science teams to optimize model performance and improve annotation processes.

Software Development Engineer role within AWS Central SDE Team, focusing on building and maintaining code for various AWS services. While AI/ML is listed as a specialization area, the core responsibilities described are general software engineering tasks. The role requires experience in designing and developing large-scale software systems and mentions knowledge of ML frameworks and fundamentals as preferred qualifications, suggesting an adjacent or exploratory engagement with AI/ML rather than core development.

Data Engineer role focused on building and maintaining scalable data infrastructure and pipelines to support ML model training and inference for fraud prevention in e-commerce. The role involves processing large volumes of data, optimizing ETL processes, ensuring data integrity, and collaborating with scientists to productionize ML models, with a focus on low latency and high reliability for inference.

Software Development Engineer role focused on robotics at Amazon, involving the design, development, and operation of innovative products and services. The role requires collaboration with cross-disciplinary teams, building scalable cloud-native solutions, and leveraging GenAI/AI tools for development productivity. Key responsibilities include working with fulfillment center technologies like robotics, computer vision, and cloud services, as well as writing clean code and participating in agile development practices.

Data Scientist role at Amazon Music focused on accelerating customer growth through personalized experiences, engagement, and retention. The role involves advanced analytics, experimentation, building causal and predictive models, and driving data-informed product decisions. It touches on Gen AI initiatives and requires experience in ML/statistical modeling and data querying.

This is a general Software Development Engineer (SDE) role within AWS that can be considered for various teams, including those focused on AI/ML. While AI/ML is mentioned as a potential specialization, the core responsibilities are for a general SDE, focusing on designing, developing, and maintaining code, implementing software solutions, and collaborating with cross-functional teams. The role emphasizes core software engineering principles and does not appear to be directly building or shipping AI models as its primary function.

This role supports ML model development by performing data annotation and assisting data scientists with classification algorithms. The focus is on ensuring high-quality annotated data to optimize model performance within the consumer domain.

The role involves performing quality audits on data submitted by Data Associates, validating automated quality measurement systems through manual reviews, and coaching Data Associates to maintain high standards of data quality for AI development and training. The primary focus is on data quality assurance for AI training.

This role is for a Sr. Analytics & AI Specialist Solutions Architect within AWS Global Sales. The primary focus is on helping customers leverage AWS services for data analytics and AI, acting as a trusted advisor and thought leader. The role involves deep technical expertise in data and AI domains to drive customer adoption and growth, collaborating with sales, marketing, and product teams. It emphasizes architectural reviews, thought leadership through content creation, and educating customers on AWS value propositions.

This role is for a Senior Solutions Architect on a new AWS Security Services team focused on driving customer adoption of AWS security services, particularly for generative AI and agentic architectures. The role involves owning the technical relationship with enterprise customers, architecting secure solutions, and providing feedback to product teams. It is a founding role on a new team, requiring the individual to help define processes and playbooks.

Senior Solutions Architect for AWS Security Services, focusing on helping enterprise customers securely adopt AWS security services, especially for generative AI and agentic architectures. This founding role involves owning technical relationships, architecting solutions, influencing product roadmaps, and producing thought leadership.

This role focuses on designing, delivering, and operating AWS cloud offerings that enable high performance and scalability for AI/ML and HPC workloads, specifically targeting continuous price-performance improvements for large-scale LLM training and inference. The candidate will work across the full technical stack from baremetal server hardware to userland software, acting as a technical leader and systems debugger.

This role focuses on building and operating AWS cloud offerings that enable high performance and scalability for AI/ML and HPC workloads, specifically targeting generative AI training and inference. The Systems Development Engineer will work on server designs, optimizing price-performance, and ensuring reliability and scalability of the underlying hardware infrastructure.

This role focuses on enabling partners and customers to deploy Generative AI (GenAI) workloads on AWS. The Partner Solution Architect will drive the go-to-market strategy for building and scaling GenAI solutions, working directly with customers to understand their challenges and implement scalable GenAI solutions, often through proof-of-concepts. The role involves collaborating with account teams, research scientists, and product teams to drive model implementations and create new solutions. Key responsibilities include enabling partners on AWS AI/data services, defining engagement strategies for autonomous agents and GenAI adoption, collaborating with AWS service teams on new capabilities, providing thought leadership on AI/data solutions, driving best practices, evangelizing partner value propositions, and offering architectural guidance for partner engagements.