In this role, you'll apply your expertise to help train next-generation AI systems. Your work will shape how models learn, reason, and perform through high-quality, real-world input. No prior experience in AI is required — your domain knowledge is what matters.
Responsibilities
Analyze and evaluate computer science problems, solutions, and applied methodologies to inform AI system training.
Author, critique, or edit technical documentation such as system design documents, research write-ups, or technical papers to ensure clarity and rigor.
Develop and review real-world computer science scenarios, datasets, and case studies for use in AI learning workflows.
Assess technical queries and propose detailed, well-structured responses based on current best practices and foundational concepts.
Collaborate with project coordinators to refine task guidelines and optimize data quality.
Provide insightful written and verbal feedback to improve model accuracy, relevance, and robustness.
Support the evaluation and continuous improvement of AI-driven tools with constructive analysis and domain expertise.
Preferred skills
BSc, MSc, or PhD in Computer Science or a closely related discipline.
Experience authoring technical papers, system design documents, or research publications.
Demonstrated expertise in a specialized domain such as algorithms, distributed systems, networking, databases, or artificial intelligence.
Exceptional written and verbal communication skills, with a passion for precise, effective expression.
Proven ability to break down complex concepts for diverse audiences and applications.
Track record of participation in collaborative research, technical reviews, or open-source contributions.
Adaptability and commitment to delivering high-quality, insightful contributions within project guidelines.
Thriveth makes AI data-training work easier to find, understand, and navigate. We replace uncertainty with clear opportunities, realistic expectations, and insights from real application journeys.
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