Data Annotator

Company Overview

Contineu is building the AI operating layer for construction. Using helmet-mounted 360° cameras and automated 3D reconstruction, our platform detects quality issues, tracks progress, and integrates Building Information Modeling (BIM) to eliminate manual data entry. We work with leading developers and contractors, transforming how field operations, quality, and planning teams work. We’re a fast-moving founding team backed by deep experience in AI, construction technology, and enterprise SaaS.

Job Summary

Contineu is looking for a Computer Vision Data Annotation Specialist to support the development and validation of AI/ML models used in construction quality assessment and civil engineering analytics. The role focuses on producing high-fidelity annotated datasets for computer vision pipelines, ensuring accuracy, consistency, and compliance with construction standards.

Responsibilities

• Perform high-precision image and video annotation using CVAT, including bounding boxes, polygons, segmentation, and attribute tagging.
• Annotate construction-site imagery related to structural elements, materials, defects, safety markers, and quality indicators.
• Ensure annotations meet defined annotation guidelines, taxonomies, and labeling schemas.
• Conduct multi-level quality assurance (self-checks and peer reviews) to validate annotation accuracy and completeness.
• Collaborate with ML engineers, product teams, and civil engineering experts to interpret data requirements and translate them into annotation tasks.
• Maintain detailed logs of annotation decisions, edge cases, and deviations to support model training and dataset versioning.
• Identify annotation inconsistencies, dataset bias, or data gaps and proactively flag them to stakeholders.
• Support continuous improvement of annotation workflows, Standard Operating Procedures (SOPs), and quality metrics.
• Participate in training and calibration sessions to align on labeling standards and improve inter-annotator agreement.

Qualifications

• Hands-on experience with CVAT or similar computer vision annotation platforms.
• Understanding of computer vision concepts such as object detection, image segmentation, and classification.
• Familiarity with ML data pipelines and the role of annotated datasets in supervised learning.
• Basic knowledge of construction or civil engineering concepts (structural components, materials, defects, site safety) is strongly preferred.
• Strong analytical skills with a high level of attention to detail and data consistency.
• Ability to work independently in a remote, distributed team environment.

Preferred Skills

• Experience annotating datasets for construction monitoring, infrastructure inspection, or quality control systems.
• Exposure to Quality Assurance (QA) metrics such as precision, recall, Intersection over Union (IoU), or inter-annotator agreement.
• Understanding of dataset versioning and annotation lifecycle management.

Experience

• Previous experience in data annotation or related fields is preferred but not explicitly required.

Environment

• This is a fully remote role with a flexible work structure.

Salary

• Estimated salary range is not specified.

Growth Opportunities

• Opportunity to work on production-grade AI systems in the construction technology domain.
• Exposure to real-world machine learning model development and validation workflows.