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DataForce by TransPerfect is part of the TransPerfect family of companies, the world’s largest provider of language and technology solutions for global business, with offices in more than 100 cities worldwide. We offer high-quality data for Human-Machine Interaction to some of the most prestigious technology companies in the world. Our department focuses on gathering, enriching, and processing data for Machine Learning in different AI domains. To learn more about DataForce please visit us at https://www.transperfect.com/dataforce . For more information on the TransPerfect Family of Companies, please visit our website at www.transperfect.com .
Education Subject Matter Expert
Location
United States
Posted
26 days ago
Salary
0
Seniority
Mid Level
No structured requirement data.
Job Description
Education Subject Matter Expert
DataForce by TransPerfect
Role Description DataForce by TransPerfect is seeking an experienced Education Subject Matter Expert (SME) with sharp analytical skills and a deep understanding of pedagogical frameworks, curriculum development (e.g., K-12 standards and higher education), learning science, and assessment design to join our AI training and model development team. The ideal candidate will bring broad expertise across multiple educational domains, from K-12 content creation and assessment to advanced academic research and curriculum design, to help train, evaluate, and fine-tune AI models. Your goal is to ensure the highest levels of pedagogical accuracy, grade-level appropriateness, curriculum alignment, and effective knowledge transfer within the AI’s output. You will work with cross-functional teams of data scientists, AI engineers, and product teams to build intelligent educational solutions such as: - Automated lesson plan generators - Dynamic study guides - Quiz and exam creation tools - Academic research assistants The goal is to construct high-quality datasets that represent realistic, end-to-end educational workflows and instructional best practices. Main Responsibilities - Domain Oversight: Serve as the primary educational authority during the training and fine-tuning of AI models, ensuring all outputs adhere to pedagogical standards, grade-level appropriate complexity (Lexile/Grade Level Fit), and correct educational terminology. - Knowledge Architecture: Develop knowledge bases, academic taxonomies, and ontologies that reflect multidisciplinary standards and complex curricular hierarchies. - Data Validation: Annotate, label, and validate datasets with specific educational knowledge, including curriculum mapping standards, clear learning objectives, and appropriate complexity for target audiences. - Prompt Engineering & Strategy: Collaborate with AI/ML engineers to design training data strategies and prompt engineering techniques specifically tailored for educational reasoning and content creation, including generating explainer texts, designing assessment rubrics, and creating lesson plans or academic papers. - Model Audit: Provide expert feedback on model outputs, identifying hallucinations, factual inaccuracies, or pedagogical flaws to improve the model’s reliability in instructional and assessment environments. - Business Alignment: Partner with product teams to align AI capabilities with educational objectives, such as automating curriculum alignment or supporting personalized learning. - Professional Watch: Stay current with emerging trends in Educational Technology (EdTech) and learning science research to ensure ethical and effective model implementation. Qualifications - Advanced degree (Master’s or PhD) in Education, Curriculum & Instruction, a specific academic discipline, or a related field. Teaching certification or equivalent experience is a plus. - 10–20 years of experience in the education sector (e.g., teaching, curriculum design, academic research, or educational content development). - Proven ability to translate complex educational standards and learning objectives into structured logic and data requirements. - Exceptional writing and verbal skills, with the ability to bridge the gap between technical AI teams and pedagogical or academic stakeholders. - Familiarity with EdTech stacks such as LMS (Learning Management Systems), digital assessment platforms, or academic research databases (e.g., JSTOR, EBSCO). - Awareness of ethical Generative AI practices, including bias detection and responsible data usage. - Familiarity with Generative AI concepts, prompt engineering, and data preparation is a plus. Benefits - Flexible hours, based on the applicant's availability. - Remote work opportunity. - Potential for project extension beyond 3 months.
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