Team Lead, Human Data Operations - Post Training

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Team Lead, Human Data Operations - Post Training based in India.

As Team Lead, Human Data Operations - Post Training, you will lead a team responsible for producing and evaluating high-quality human data that supports the development of advanced AI systems. You will own quality and delivery across assigned projects, combining hands-on review with team leadership and operational improvement. The role requires you to set high standards for accuracy, consistency, and adherence to detailed guidelines while ensuring efficient delivery at scale. You will coach and develop AI Tutors, manage performance, and foster a culture of accountability and continuous improvement. Working closely with Human Data Managers, fellow Team Leads, and Engineering, you will translate evolving model requirements into effective data strategies. This is an opportunity to make a direct impact in a highly motivated, engineering-focused environment where initiative, curiosity, and execution are highly valued.

Accountabilities

• Own end-to-end quality and delivery for assigned Human Data projects, personally reviewing domain-specific work and ensuring accuracy, consistency, guideline adherence, and high-quality data production at scale.
• Lead, coach, and performance-manage a team of AI Tutors through regular reviews, documented feedback, action plans, shadow sessions, and continuous development.
• Participate directly in labeling, annotation, and review activities to maintain quality standards and demonstrate best practices.
• Establish and maintain rigorous guideline adherence, taxonomy management, and quality assurance processes.
• Monitor team and project performance through KPIs such as quality scores, throughput, send-back rates, and other operational metrics.
• Identify operational bottlenecks and implement process improvements to increase efficiency, quality, and scalability.
• Create, maintain, and deliver training materials, practice exercises, and certification benchmark tasks.
• Manage certification processes and make workforce adjustments based on performance, project needs, and operational requirements.
• Collaborate with Human Data Managers, other Team Leads, and Engineering teams to translate model requirements into clear labeling strategies and operational guidelines.
• Develop team capabilities while maintaining strong accountability and a high-performance culture, including supporting disciplinary processes when necessary.
• Document project outcomes, identify opportunities for process iteration, and communicate project status, risks, and results to relevant stakeholders.
• Represent the needs and perspectives of AI Tutors while fostering effective collaboration across the wider Human Data organization.
• Balance strategic thinking with hands-on execution in a fast-moving environment where priorities may evolve quickly.

Requirements:

• At least 1 year of hands-on experience in data labeling, annotation, AI training or evaluation, content quality, or a similar operational environment.
• Bachelor’s degree or at least 4 years of relevant professional experience in place of a degree.
• Demonstrated understanding of data quality metrics, annotation processes, and guideline-driven workflows.
• Basic understanding of artificial intelligence and machine learning concepts, particularly the relationship between training data quality and model performance.
• Familiarity with project management and collaboration platforms such as Notion, Axiom, JIRA, Linear, or equivalent tools.
• Previous experience leading or mentoring small teams in data labeling, annotation, content quality, or related operations is highly valued.
• Strong domain expertise in at least one relevant field, such as design, psychology, philosophy, writing, or another humanities discipline, is preferred.
• Proven ability to manage multiple concurrent projects and prioritize effectively in a fast-paced environment.
• Strong experience reviewing domain-specific work, maintaining data quality, and improving operational processes.
• Experience with coaching, performance management, training development, and certification programs is an advantage.
• Strong analytical capabilities and the ability to use data and KPIs to identify trends and drive continuous improvement; SQL knowledge is a plus.
• Experience managing distributed teams is desirable.
• Excellent written and verbal communication skills, with the ability to build rapport, communicate clearly, and align diverse stakeholders.
• Exceptional organizational skills and attention to detail.
• Proactive and structured approach to problem-solving, with a strong focus on continuous improvement.
• Ability to combine strategic thinking with hands-on execution.
• Strong interest in developing high-performing teams and scaling reliable, high-quality Human Data operations.
• Fluent English communication skills.
• Ability to work effectively in a highly collaborative, flat, and fast-moving environment where initiative and ownership are expected.

Benefits:

• Fully remote working opportunity, subject to applicable employment and location requirements.
• Competitive compensation, with international salary details shared during the recruitment process.
• Equity participation as part of the overall rewards package, where applicable.
• Comprehensive medical, dental, and vision coverage for eligible employees, depending on location and employment type.
• Access to retirement benefits such as a 401(k) plan for eligible U.S.-based positions.
• Short- and long-term disability insurance and life insurance for eligible employees.
• Paid sick leave and additional benefits depending on location and jurisdiction.
• Various employee discounts, perks, and additional rewards.
• Opportunity to work at the intersection of AI, human data, and advanced machine learning systems.
• Direct impact on the quality of data used to train and evaluate next-generation AI models.
• Opportunity to lead and develop a high-performing distributed team.
• Hands-on exposure to complex AI training and evaluation operations.
• Fast-paced environment with significant opportunities to contribute ideas, improve processes, and take ownership.
• International and collaborative working environment.