Amazon

Software Development Engineer (Java/AWS) for Alexa AI team, focusing on building and delivering innovative consumer software products and industry-leading conversational assistant capabilities. The role involves owning large-scale customer-facing features, designing and architecting innovative consumer products, and contributing to the core runtime orchestration platform for conversational agents using LLMs and Gen AI.

Principal Solutions Architect for AWS, focusing on financial services in Central Eastern Europe. The role involves leading technical strategy, architecting and implementing cloud solutions, and guiding customers in adopting agentic AI workloads, autonomous systems, and intelligent automation. Key responsibilities include designing scalable, secure, and compliant architectures, championing innovation with agentic architecture patterns and AI-SDLC methodologies, and translating business challenges into cloud-native solutions. The role also involves thought leadership, mentoring other Solutions Architects, and contributing to the AWS knowledge base.

Software Development Engineer role focused on building and scaling AI-powered computer vision cloud services for Ring consumer electronics, serving tens of millions of users globally. Responsibilities include product definition, design, development, deployment, and operations of highly available and resilient cloud services.

Software Development Engineer role focused on building and delivering consumer-facing conversational assistant features using advanced LLM techniques like fine-tuning and prompt optimization for Alexa AI.

This role is a Team Manager for Data Services within Amazon's Artificial General Intelligence (AGI) organization. The team focuses on data creation, curation, and analytics to support the development and training of Alexa AI, specifically improving speech recognition and language understanding capabilities. The manager will oversee daily operations, hiring, training, performance monitoring, scheduling, and process improvement, working closely with ML Science teams. While the team supports AI development, the manager's core responsibilities are operational and people management, not direct AI/ML model building.

This role focuses on consulting with AGI-DS scientists on ML/Gen AI data collections, managing customer relationships, and driving business value through technical advisory. The lead will transform research objectives into data collection requirements, coordinate delivery, and monitor collection health metrics. While it involves ML data operations and understanding ML workflows, the core function is product management and customer advisory for data solutions, not direct AI model building or research.

This role is a Data Solutions Lead at Amazon, focusing on ML/Gen AI data collections and customer relationships. The lead will consult with AGI-DS scientists, manage workstreams for data collection requirements, and ensure seamless delivery. Key responsibilities include driving effective ML/GenAI solutions, coordinating across teams, owning customer scientist relationships, providing consultation on ML workflow capabilities, and monitoring collection health metrics. The role also involves guiding customers on workflow feasibility, collaborating on technical requirements, evaluating annotation scenario scalability, and influencing technical documentation.

The AI Data Associate role focuses on foundational labeling tasks for generative AI and LLMs, including dialogue evaluation across text, speech, audio, image, and video data. The role involves maintaining confidentiality, delivering high-quality labeled data using in-house tools, analyzing root causes of errors, and proposing solutions to improve labeling quality and operational processes. The goal is to support the development and responsible deployment of AI by providing essential data.

The AI Data Associate role focuses on foundational labeling tasks for generative AI, including dialogue evaluation across text, speech, audio, image, and video data. The role involves maintaining data quality, analyzing root causes of errors, and suggesting process improvements, all while adhering to strict confidentiality and Amazon's policies for responsible AI development.

The AI Data Associate role focuses on foundational labeling functions for generative AI and LLMs, including dialogue evaluation across text, speech, audio, image, and video data. The role involves maintaining confidentiality, delivering high-quality labeled data using in-house tools, analyzing root causes of errors, and proposing solutions to enhance labeling quality and operational processes. The position requires C1+ French fluency and B2+ English proficiency, with a focus on analytical thinking, attention to detail, and structured problem-solving.

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.

Software Development Engineer in Test focused on AI-enhanced automation for camera SDKs, aiming to improve test frameworks, efficiency, and defect detection in embedded systems.

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.

This Engagement Manager role leads Generative AI transformation projects for AWS customers, focusing on driving adoption, orchestrating engagements, and ensuring successful delivery of AI solutions. The role involves developing AI adoption strategies, leveraging AWS Foundation Models and LLM solutions, and managing cross-functional teams. It is a customer-facing product role focused on delivering business outcomes through AI.

This role involves performing quality audits and manual reviews of data processed by Data Associates to ensure high standards for AI development and training. It requires coaching Data Associates, identifying root causes of quality issues, and validating automated quality measurement systems. The role emphasizes attention to detail, analytical skills, and compliance with quality standards.

This role focuses on quality auditing for AI data services, involving manual review and validation of automated quality measurements to ensure high standards in data quality for AI development and training. It requires experience in ML/Data Labeling operations and understanding of data annotation and quality metrics.

This role focuses on quality auditing for AI data services, involving manual review and validation of automated quality measurements to ensure high standards in data quality for AI development and training. It requires experience in ML/Data Labeling operations and understanding of data annotation and quality metrics.

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.

This role is for a Senior Solutions Architect Manager at AWS, focusing on leading a team of Solutions Architects to help customers leverage AWS services and generative AI to achieve business outcomes. The role involves building and leading teams, developing strategic customer relationships, acting as a technical thought leader, and guiding the design and implementation of cloud solutions with a focus on emerging technologies like generative AI.

This role is a Team Manager for Data Services within Amazon's Artificial General Intelligence (AGI) organization. The team focuses on data creation, curation, and analytics to support the development and training of Alexa AI, specifically improving speech recognition and language understanding capabilities. The manager will oversee daily operations, hiring, training, performance monitoring, scheduling, and process improvement, working closely with ML Science teams. While the team supports AI development, the manager's core responsibilities are operational and people management, not direct AI/ML model building.

The AI Data Associate role focuses on foundational labeling tasks for generative AI, including dialogue evaluation across text, speech, audio, image, and video data. The role involves maintaining data quality, analyzing root causes of errors, and suggesting process improvements, all while adhering to strict confidentiality and Amazon's policies for responsible AI development.

This role involves foundational labeling of diverse data types (text, speech, audio, image, video) for generative AI and LLMs, focusing on quality, accuracy, and confidentiality. The associate will use in-house tools, analyze data patterns, identify process improvements, and provide floor support. The goal is to contribute to Amazon's responsible AI development.

Software Development Engineer in Test focused on AI-enhanced automation for camera SDKs, including audio/video pipelines, secure boot, and hardware abstraction layers, aiming to improve test coverage, reduce execution time, and enhance defect detection.

The role involves foundational labeling functions for generative AI and LLMs, including dialogue evaluation on speech, text, audio, image, and video data. The associate will maintain confidentiality, deliver high-quality labeled data using in-house tools, analyze root causes of errors, and propose solutions to enhance labeling quality and operational processes. The role requires strong analytical thinking, attention to detail, and the ability to interpret and implement detailed instructions.

This role focuses on establishing and maintaining quality frameworks for AI data services, defining quality metrics, analyzing data trends, and partnering with teams to optimize workflow quality. It involves creating prescriptive actions for quality issues and evaluating quality tools. While the company is involved in generative AI, this specific role is centered on data quality assurance and process improvement, not direct AI/ML model development or research.

This role focuses on data quality within Amazon's AGI Data Services, ensuring comprehensive quality frameworks and optimizing workflows. Responsibilities include defining quality metrics, creating actions for issues, partnering with teams, analyzing data trends, monitoring performance, handling escalations, and suggesting improvements for quality tools. While the company is investing in generative AI and LLMs, this specific role is centered on data quality assurance and process optimization, not direct AI/ML model development or research.

Solutions Architect for AWS Public Sector, focusing on helping customers architect and implement solutions on the AWS platform. This role involves technical engagement, understanding customer needs, and ensuring successful project delivery.

This role is for a Senior Training Specialist responsible for facilitating blended learning, managing training logistics, tracking completion via an LMS, and identifying areas for training improvement within the AGI-DS organization. The role involves developing and documenting processes to enhance training delivery and collaborating with stakeholders to ensure trainee success.

This role is for a Senior Training Specialist focused on facilitating blended learning for the AGI-DS organization, which deals with generative AI and LLMs. The responsibilities include planning, scheduling, coordination, and execution of training, tracking completion through an LMS, identifying areas for improvement, and driving innovation in training approaches. The role requires proficiency in both English and French, strong communication and organizational skills, and knowledge of adult learning practices. While the organization works with AI, the role itself is focused on training delivery and management, not direct AI/ML development.