Data Annotation Team Lead

We’re looking for a Data Annotation Team Lead to manage and develop a team of eight data annotators and partner closely with Machine Learning, Legal Engineering, Product, and Engineering teams. This role combines people leadership, project management, and quality management. The ideal candidate can create clear processes while maintaining a supportive environment built on trust, ownership, and open communication. Compensation starts at 100,000 CZK per month, with the final offer determined by the candidate’s seniority and experience. Key Responsibilities Lead, coach, and develop the Data Annotation team through regular 1:1s, clear expectations, and timely feedback Build an environment where team members feel comfortable asking questions, raising concerns, and sharing ideas Own hiring, onboarding, performance management, and professional development for the team Work with ML, Legal Engineering, and Product teams to translate project goals into clear annotation requirements Define project ownership, timelines, quality standards, responsibilities, and escalation paths Help the team resolve ambiguous cases, remove blockers, and make timely decisions Create and maintain annotation guidelines, quality rubrics, training materials, and review processes Track quality, capacity, and delivery using practical metrics that support the team Run calibration sessions, retrospectives, and quality reviews, ensuring feedback leads to clear follow-up actions Communicate project progress, risks, and staffing needs to stakeholders Requirements Proven experience managing, coaching, and developing a team Strong professional English and fluency in Czech or Slovak Strong communication skills and the ability to handle feedback, disagreement, and difficult conversations constructively Experience setting clear expectations and addressing performance concerns directly and fairly Strong organizational and project-management skills Ability to create useful structure without introducing unnecessary complexity Good judgment and confidence making decisions in ambiguous situations Experience working with quality, productivity, or operational metrics Ability to collaborate effectively with both technical and non-technical teams Strong attention to detail and commitment to accuracy and consistency Interest in artificial intelligence, machine learning, and human-in-the-loop workflows