Amazon

This role focuses on language data, primarily in the areas of text annotation and general data analysis deliverables for Alexa AI. The ML Data Linguist will handle unique data analysis requests, provide data quality expertise, and contribute to process improvements. Responsibilities include labeling, generating, and ensuring the quality of datasets, working with ML Data Linguists and scientists to resolve annotation guideline issues, and conducting qualitative error trend analysis.

This role focuses on applying expertise in human visual perception to guide the design, evaluation, and optimization of next-generation display systems and visual experiences for Amazon's device portfolio. It involves developing computational models of human vision, designing psychophysical experiments, analyzing data, and building perceptual simulation pipelines to inform display hardware and software decisions. The role bridges vision science, computational modeling, display engineering, and user experience, translating perceptual principles into product specifications.

Software Development Engineer II role focused on the user-space software for Elastic Fabric Adapter (EFA) network cards, crucial for Machine Learning (ML) and High-Performance Computing (HPC) customers on AWS. The role involves writing high-performance C code for open-source projects, inventing new networking APIs, optimizing for low latency and high bandwidth, and supporting major AI companies. The team is part of Annapurna Labs and focuses on enabling next-generation ML in the cloud.

This role focuses on business intelligence and data analysis for Amazon's promotions and events. The engineer will develop analytical reporting, conduct deep dives, and leverage LLMs to generate insights and drive growth discussions. The role also involves improving data sources and ensuring data quality. While the role uses LLMs, its core function is business intelligence and data engineering, not direct AI model development.

Associate Support Engineer role focused on technical support for AWS Region Services, involving troubleshooting, interacting with engineers, leveraging Linux experience, driving service team communication, and improving support processes. The role also involves writing technical articles, coaching new hires, and using internal AI systems for problem-solving.

This role manages a team responsible for the deployment automation of Wireless and Access networks within Amazon's Operations Technology. The focus is on transforming innovative network designs into production-ready implementations that support a wide range of technologies including robotics, industrial IoT, sensors, drones, and mobile devices. The role involves setting technical vision, driving operational excellence through automation, partnering with internal and external teams for innovation, and establishing engineering metrics for service health and performance. While AI and ML are mentioned as tools to enhance network automation and operations, the core function is network engineering and management, not direct AI/ML model development.

Lead Software Development Engineer for Audible's Playback team, focusing on core playback logic, services, and audio ad systems. The role involves designing, architecting, and implementing machine learning solutions for audio advertising at scale, optimizing ad serving, and integrating conversational AI. Requires strong software development, system design, and leadership skills.

This role focuses on developing and executing go-to-market strategies for AWS partners in the Agentic AI and AI Security space. It involves collaborating with partners to implement agent-based solutions, driving adoption, and providing thought leadership on business model transformation. The role also includes building enablement programs and analyzing market trends to inform AWS's AI strategy.

The role involves foundational labeling functions for generative AI and LLMs, including dialogue evaluation on speech, text, audio, and video data. The candidate will work with various data types, deliver high-quality labeled data using in-house tools, and analyze root causes to improve labeling quality. The role requires strong analytical thinking, problem-solving, and attention to detail, with fluency in Dutch and English.

The AI Data Associate will be responsible for foundational labeling functions, including dialogue evaluation on speech, text, audio, video data, to support the development and deployment of generative AI and LLMs at Amazon. This role involves working with diverse data types, delivering high-quality labeled data, analyzing root causes of errors, and proposing solutions to enhance labeling quality.

Senior Sales Specialist for GenAI/ML on AWS, focusing on driving customer adoption and revenue growth for AWS Generative AI services within a specific territory. This role involves identifying customer opportunities, understanding their needs, positioning AWS solutions, and acting as a trusted advisor to embed and deploy GenAI services. Responsibilities include developing GTM strategies, engaging with C-suite leaders, creating value propositions, and gathering customer insights to inform product roadmaps.

This role focuses on improving global logistics and delivery experiences by building and validating predictive and classification models using machine learning techniques. It involves feature engineering, exploratory data analysis, and partnering with operations teams to implement ML solutions within Amazon's fulfillment and delivery network.

This role focuses on building business intelligence and analytics solutions for Amazon's satellite broadband network (Amazon Leo). The Senior Business Intelligence Engineer will architect and deliver data-driven insights to streamline production operations, develop key metrics, build self-service reporting, and create data pipelines. While the role requires staying current with AI/ML advancements and evangelizing new technologies, its core function is data engineering and business intelligence, not direct AI/ML model development or deployment.

The Senior Business Intelligence Engineer (Sr. BIE) on the Amazon Just Walk Out (JWO) team is a strategic technical leader responsible for designing and delivering scalable business intelligence solutions that drive data-informed decision-making across the JWO organization. This role combines deep technical expertise in data engineering, analytics, and visualization with strong business acumen to transform complex data into actionable insights. The Sr. BIE partners with leadership, product teams, operations, and engineering to build robust reporting frameworks, automate data pipelines, and enable self-service analytics that support the growth and optimization of Amazon's cashierless retail technology platform.

This role manages a team responsible for developing and scaling AWS' Machine Learning infrastructure through strategic colocation partnerships. It involves managing the lifecycle of ML-focused colocation deals, ensuring operational excellence, contractual compliance, and infrastructure reliability for ML workloads. The role collaborates with various internal teams and external partners to optimize colocation strategies supporting AWS' ML service scaling.

Product Manager for Amazon Pay's Customer Trust team, focusing on fraud and abuse prevention using machine learning and advanced analytics. Responsibilities include defining product features, partnering with engineering, and delivering complex product solutions to protect customer trust and business growth.

This role is for a Senior National Account Manager at Amazon's Ring and Blink division, focusing on driving retail growth through strategic account management and leveraging AI/ML tools for sales analysis, trend prediction, and inventory optimization. The role involves cross-functional collaboration with retailers and internal teams, developing promotional and marketing strategies, and driving the adoption of AI-enabled analytics for product placement and pricing.

This role focuses on analyzing data, detecting anomalies, and preventing fraudulent activity on Amazon's platform by deploying rules and leveraging machine learning systems. It involves working with large datasets, identifying patterns, and collaborating with product managers, scientists, and engineers to maintain customer trust and prevent bad actors.

This role is for a Senior Enterprise Account Manager focused on AI Models and Foundation Model Providers on AWS. The primary responsibilities include managing strategic relationships, driving revenue and adoption, and acting as a trusted advisor to AI companies. The role requires a blend of sales and technical expertise to engage with C-level executives and AI developers.

This role is for a Principal Enterprise Account Manager focused on AI Model Providers within the HiTech industry. The primary responsibility is to manage strategic relationships with AI companies, driving revenue, adoption, and market penetration on AWS. The role requires a blend of sales and technical expertise to engage with C-level executives, developers, and engineers, and to lead cross-functional teams in shaping strategies for partners, professional services, and training. The goal is to help enterprise AI-native companies scale their infrastructure and go-to-market efforts.

This role focuses on defining and executing Go-to-Market (GTM) strategies for Generative AI (GenAI) solutions on AWS. The specialist will engage with customers, product owners, and GenAI model providers to influence product direction, develop proofs-of-concept, and drive the adoption of GenAI services. The role requires a blend of business and technical expertise to articulate the value of GenAI solutions and market trends to diverse audiences, including C-level executives.

This role is for a Business Intelligence Engineer on the Alexa Enterprise Data team. The primary focus is on defining metrics and KPIs, and performing deep-dive analyses on large datasets to provide actionable insights to business stakeholders. The role involves building and maintaining automated reporting solutions and data pipelines, with a strong emphasis on SQL, ETL, and data wrangling. While the team works with Generative AI and LLM capabilities, this role is primarily focused on the data infrastructure and insights generation rather than direct AI/ML model development.

This role focuses on auditing and optimizing machine learning data workflows, acting as a deep expert in 1-2 workflows and leading quality audit teams. It involves hands-on audit execution, analysis of data quality, and providing insights for workflow improvement.

The role involves performing quality audits and manual reviews on data provided by Data Associates to ensure data quality for AI development and training. It also includes coaching Data Associates and validating automated quality measurement systems.

The role involves performing quality audits and manual reviews on data provided by Data Associates to ensure data quality for AI development and training. It also includes coaching Data Associates and validating automated quality measurement systems.

Solutions Architect role focused on guiding enterprise customers in the Benelux region on their Generative AI transformation, helping them adopt agile operation models and build modern SaaS architectures using AWS services. The role involves building technical relationships, acting as a trusted advisor, and sharing customer needs internally to inform AWS roadmaps. It also includes creating and sharing best practices, technical content, and reference architectures, as well as evangelizing AWS technology.

Director of Sales Operations for AWS Japan, focusing on driving long-term business growth through data analysis, forecasting, and optimizing business processes. The role involves supporting Generative AI initiatives to unlock data-driven insights and customer innovation, but the core function is sales operations and strategy, not direct AI/ML model development.

This role is for a Sr. Software Engineer on the EFA Network ML Software Team at Amazon. The team owns the user-space software for the Elastic Fabric Adapter (EFA) network card, enabling customers to network thousands of GPU and CPU instances for ML and HPC workloads. The engineer will write high-performance C code for open-source projects, invent new networking APIs, and provide expert support to AI customers. The role involves leading design and architecture, focusing on performance, low latency, and high bandwidth in clustered environments.

This role focuses on managing risks associated with AI and machine learning models and processes, ensuring compliance with regulatory requirements and internal standards. It involves working with stakeholders to identify risks, manage use cases, maintain inventories, and provide training on AI/ML risk management.

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 a Technical Go-To-Market (GTM) Specialist for AWS's automotive compute portfolio, focusing on Autonomous Vehicles (AV), Advanced Driver Assistance Systems (ADAS), Software-Defined Vehicles (SDV), and Electrical/Electronic (E/E) architecture workloads. The specialist will own the end-to-end GTM strategy, drive revenue pipeline acceleration, build mechanisms for business outcomes, and work directly with customers and partners. A key responsibility is articulating the value of Generative AI in accelerating automotive software development.

Account Manager for AWS Startups, focusing on driving adoption and revenue for AWS cloud services among early-stage, high-potential startups. The role involves advising founders on technical innovations like generative AI and machine learning, and working with various internal and external stakeholders to ensure customer success and business growth.

Senior Financial Analyst role focused on competitive intelligence and sales analytics for AWS. The role involves building financial models, analyzing public company disclosures, and supporting sales pipeline analysis. A key aspect is leveraging Generative AI as a daily production tool to build and maintain scalable mechanisms for executive-quality outputs, including co-producing a GenAI-powered intelligence newsletter.

This role is for a Sr. Risk Manager in Amazon's lending portfolio, focusing on adverse risk actions and building a credit program. It involves strategic planning, cross-functional leadership, data-driven innovation, and leveraging AI/ML tools, specifically an AI Agent, to automate tasks and improve decision-making. The role requires partnering with Science teams to design features and build automated credit decisioning systems, acting as a power user for AI-enabled tools.

Account Manager for AWS, focusing on helping software startups grow and scale on the AWS cloud platform. The role involves driving revenue, promoting AWS services, and understanding customer needs, including trends like AI/ML.

This role is for a Sr. Analytics/AI Specialist Solutions Architect at Amazon Web Services (AWS). The primary focus is on helping customers leverage AWS services, particularly in analytics and Generative AI, to solve complex business problems. The role involves deep technical expertise, customer collaboration, architectural reviews, and thought leadership. While AI is mentioned as a differentiator and a tool used by Amazon for over 20 years, the core function of this role is to enable customer adoption and growth of AWS services, acting as a trusted advisor and subject matter expert in analytics and cloud computing.

Product Marketing Manager for an enterprise AI platform combining generative AI search, research, agents, and business intelligence. The role involves shaping go-to-market strategy, influencing product strategy, understanding customer needs, and developing messaging for AI chat, research agents, workflow automation, and analytics capabilities.

This role is for a Sr. TPM at Amazon, AWS Builder Acceleration (AWSBA) team, focused on simplifying and accelerating the software development experience for AWS engineers using GenAI and advanced AWS technologies. The goal is to reduce toil, increase building efficiency, and eliminate friction in the software development and operational lifecycle through AI-based automated solutions.

Senior Technical Product Manager for Amazon's Selling Partner Services, focusing on the front-end seller experience. The role involves defining product strategy, roadmap planning, and requirements definition for a platform used by millions of sellers. While the role leverages and identifies opportunities for AI tools, its core function is product management for a customer-facing platform, not direct AI/ML model development or research.

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.

Product Manager role focused on creator partnerships and monetization on Amazon, with an emphasis on leveraging generative AI tools for workflow efficiency and product enhancement.

Senior Product Manager, Technical for Amazon Music CX Infrastructure, focusing on Playback, Mobile Architecture, and Innovation Velocity. This role involves leveraging Generative AI to enhance developer velocity and build AI-powered tools for processing customer feedback and driving improvements through the development cycle. The goal is to define the next generation of software development at Amazon Music where AI acts as a force multiplier.

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.