What You'll Do
- Team Leadership & Mentorship
- Supervise a team of 25+ annotation technicians, setting clear goals, conducting regular reviews, and fostering professional development.
- Coordinate cross-training opportunities to deepen team expertise across modalities (2D/3D/image/video).
- Workflow Design & Optimization
- Define, document and continually refine annotation guidelines and SOPs for multi-modal data (e.g., bounding boxes, segmentation masks, keypoints, 3D cuboids).
- Identify bottlenecks, implement automation where possible (scripts, QA checks), and scale workflows to meet growing data demands.
- Quality Assurance & Standards
- Establish and enforce quality metrics (accuracy thresholds, inter-annotator agreement) to maintain dataset integrity.
- Lead periodic audits, root-cause analyses, and corrective-action plans.
- Cross-Functional Collaboration
- Work alongside Machine Learning engineers and research scientists to tailor annotation schemas for new model architectures and sensor suites.
- Liaise with Product and Operations to prioritize data requirements for upcoming feature releases.
- Data & Tooling
- Oversee tooling selection and customization.
- Coordinate with software engineers and data scientists to integrate Python or SQL-based analytics for annotation reporting, throughput tracking, and trend analysis.
Essential Qualifications
- 2 + years hands-on experience annotating data for machine-learning: images, video, and/or 3D point clouds.
- Demonstrated expertise in end-to-end annotation workflows
- Proven track record leading small to mid-sized teams (5–25 people), including hiring, performance reviews, and coaching.
- Deep understanding of annotation quality metrics and QA methodologies.
- Must have legal right to work in Rwanda
Preferred Skills & Experience
- Bachelor’s or Master’s in Data/Computer Science, Engineering, or related field.
- Familiarity with commercial annotation tools (e.g., Encord, Segments.ai, Labelbox 3D, Scale AI).
- Experience with Python scripting for annotation-related automation or tooling.
- Proficiency in SQL for data analysis and reporting.
- Background in UAV operations, autonomy research, or logistics.
- Knowledge of best practices in data security and privacy.
Salary
Competitive
Monthly based
Location
Kigali, Kigali City, Rwanda
Job Overview
Location
Kigali, Kigali City, Rwanda
