Role Description We are seeking a talented and detail-oriented Cantonese AI Voice Contributor to support AI and machine learning projects through high-quality voice recordings. Your recordings will help train and improve speech recognition, conversational AI, and language technology systems. The ideal candidate is a native Cantonese speaker with clear pronunciation, strong reading skills, and the ability to deliver natural, authentic speech across a variety of recording tasks. - Record scripted and conversational voice content in Cantonese. - Produce natural and accurate speech recordings. - Follow project guidelines and pronunciation standards. - Review recordings for quality and completeness before submission. - Meet recording targets and project deadlines. - Report technical or script-related issues when necessary. Qualifications - Native or near-native Cantonese speaker. - Excellent articulation and pronunciation. - Strong reading comprehension and attention to detail. - Reliable internet connection and access to a quiet recording environment. - Ability to work independently and follow instructions. Requirements - Experience in voice recording, AI projects, or language-related work. - Familiarity with recording software. - Professional recording equipment. Company Description

Role Description We are looking for detail-oriented Trainers to support an AI data annotation project. In this role, you will review pre-seeded questions paired with images and provide accurate "golden" answers based on what you observe in the image. - Review images and pre-seeded questions. - Analyze image content and provide accurate "golden" answers. - Flag unclear or unusable images. - Ensure quality, accuracy, and consistency. - Follow project guidelines and instructions. Qualifications - Strong/native proficiency in Sanskrit. - Fluent English (reading and writing). - Bachelor's degree. - Excellent attention to detail. - Ability to follow instructions accurately. - Reliable computer and internet access. - Data annotation/labeling experience is a plus. Requirements - Freelance, Remote - 10 hours/week - $26.40/hour - Long-term Company Description Join our team at Welo Data and embark on a journey of growth and innovation.

• Reporting into the VP, Head of Analytics and AI, the Executive Director, Applied AI is a senior leadership role responsible for building, operating, and scaling CRG Digital’s end-to-end AI engineering and platform capability, anchored in reusable architecture and scalable execution systems. • This includes ownership of AI engineering delivery, platform architecture, and the integrated automation layer—ensuring that AI-enabled solutions are production-ready, scalable, and seamlessly embedded into business operations. • Operating at the intersection of Applied AI (AAI), Data, and Product Engineering, this leader unifies solution delivery and platform enablement into a cohesive, high-performing system. • The role is accountable for both what gets built and how it runs, combining product-aligned engineering teams with a robust, reusable platform that accelerates development, enforces standards, and enables federated AI adoption across CRG. • A core part of this mandate is defining and scaling reusable AI architecture patterns, services, and components that support rapid development of AI-enabled capabilities across domains. • A strong focus of this role is the development of a modern AI-native execution layer, where AI-driven decisioning, services, and workflows are operationalized through APIs, orchestration frameworks, and automation capabilities.

• Building, operating and scaling CRG Digital’s end-to-end AI engineering and platform capability • Ownership of AI engineering delivery, platform architecture, and the integrated automation layer—ensuring that AI-enabled solutions are production-ready, scalable, and seamlessly embedded into business operations • Unifying solution delivery and platform enablement into a cohesive, high-performing system • Defining and scaling reusable AI architecture patterns, services, and components that support rapid development of AI-enabled capabilities across domains • Development of a modern AI-native execution layer, where AI-driven decisioning, services, and workflows are operationalized through APIs, orchestration frameworks, and automation capabilities • Establishing a target operating model where individual engineers are significantly amplified by AI tooling • Partnering with Solution Architecture to translate AI use cases into scalable technical solutions and ensuring solutions are designed for real-world workflow integration • Building and scaling a modern AI-native execution layer that operationalizes AI-driven decisions into real-world actions