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Generalist ML title and mid-level (3–7 yrs) increase competition despite niche construction CV focus.
Core computer vision skills transfer across industries, though construction domain knowledge moderately increases specificity.
Explicit 3–7 years and mandatory CV model and deployment skills make shortlisting strict.
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Design, develop, and deploy AI-powered computer vision solutions across construction workflows using diverse data types (images, videos, LiDAR, 3D data).
Build, optimize, and fine-tune models including CNNs, Vision Transformers, DETR, YOLO, Mask R-CNN, and foundation vision models for image/video analytics and multimodal AI.
Manage dataset engineering tasks including annotation strategy, data augmentation, and quality validation to enhance model performance.
3–7 years of experience in Computer Vision.
Strong programming skills in Python and hands-on AI/ML development experience.
Proficiency with deep learning frameworks and modern architectures (CNNs, Vision Transformers, foundation vision models).
Experience with dataset preparation, annotation, augmentation, GPU-based training, and deploying production AI models.
Experienced in deploying production-grade computer vision solutions in real-world applications, preferably in construction or engineering contexts.
Skilled in end-to-end AI lifecycle including dataset creation, model training, optimization, and collaboration with cross-functional teams.
Capable of working with cutting-edge foundation vision models and multimodal AI systems combining vision and language components.