About this Data Annotation Team Lead role at Filevine
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.
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
