Project Lead - Annotation

Position Summary

As a Project Lead Annotation, you will be responsible for leading large, distributed teamsboth internal and vendor-basedin delivering high-quality annotated datasets for AI and machine learning projects. You will oversee end-to-end project execution, define annotation workflows, configure QA pipelines, and ensure consistent throughput and data accuracy.

This role requires a strong blend of team leadership, process orientation, and hands-on technical know-how of annotation platforms and data labeling tools. The ideal candidate is a structured thinker, effective communicator, and passionate about enabling AI development through precise human-in-the-loop data handling.

Key Responsibilities

• Lead and manage large annotation teams, including third-party vendors and remote contributors
• Assign tasks, define milestones, track progress, and manage workloads to ensure on-time delivery
• Motivate and train team members, fostering a culture of ownership and continuous improvement
• Draft and maintain clear annotation guidelines and ensure adherence across the team
• Design and implement QA strategies to monitor and enhance data quality and consistency
• Optimize workflows, review loops, and escalation paths to improve labeling efficiency
• Collaborate with cross-functional teams including product managers, engineers, and QA leads
• Propose and implement process improvements to enhance throughput and accuracy
• Monitor metrics, analyze team performance, and recommend corrective actions
• Utilize collaboration tools to manage distributed workflows effectively

Qualifications & Experience

• Bachelors or masters degree in computer science, Information Technology, Data Engineering, or a related field
• 3-6 years of experience leading data or annotation projects, with proven experience managing distributed teams
• Hands-on experience with annotation tools such as Label box, CVAT, or other custom labeling platforms
• Strong understanding of data formats such as JSON, XML, YOLO, CSV, and COCO
• Experience in configuring QA workflows, writing annotation guidelines, and driving performance-based output
• Knowledge of AI and machine learning concepts, including RLHF (Reinforcement Learning from Human Feedback)
• Excellent communication and interpersonal skills to work with global teams and clients
• Strong problem-solving, organizational, and multitasking skills

What We Offer

• Competitive compensation package aligned with your experience and contribution
• Flexible benefits to support your professional and personal goals
• A collaborative, experimentation-driven work culture
• Co-funded learning and upskilling programs to accelerate your career.