Data Labeling Team Lead

About Us: We are a cutting-edge company that specializes in providing high-quality training datasets to fuel the next generation of AI models. Our clients range from startups to top-tier tech giants, all relying on our expertise to deliver clean, structured, and domain-rich data.

We’re looking for an experienced and proactive Annotation Data Lead to establish and manage a team focused on creating, curating, and validating educational training data. This role requires a blend of academic rigor, operational leadership, and deep attention to detail.

You’ll be responsible for setting up the team from scratch – hiring, training, managing workflows, and ensuring quality delivery of datasets that will be used to train advanced AI models.

The Core Job

• Build and Lead the Team: Recruit, onboard, and manage a team of subject matter experts (SMEs), content creators, and data annotators in Math, Physics, Chemistry, and standardized test preparation.
• Own the Process: Design scalable processes for dataset creation, QA, annotation, and formatting, ensuring alignment with client and internal requirements.
• Content Oversight: Guide the creation of high-quality, diverse educational content including questions, explanations, problem-solving steps, and structured answers.
• Quality Assurance: Implement rigorous review and validation standards to ensure data accuracy, clarity, and pedagogical soundness.
• Cross-functional Collaboration: Work closely with product, engineering, and data science teams to understand data format requirements, use cases, and feedback loops.
• Continuous Improvement: Identify opportunities to automate, improve efficiency, and expand content coverage and complexity.

• Bachelor’s or Master’s degree in a STEM field (Math, Physics, Chemistry, Engineering, etc.) or equivalent experience.
• 4+ years of experience in educational content development, curriculum design, or training data creation for AI/ML.
• 2+ years of experience managing or leading teams.
• Strong understanding of academic standards, AP curriculum, or standardized tests like SAT, ACT, etc.
• Exceptional attention to detail and quality control.
• Excellent written and spoken English (IELTS >= 7.5 or TOEIC >= 900 or equivalent)
• Familiarity with AI/ML concepts, data annotation processes, and large language models is a plus.