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Mid-level ML role with moderate brand and specialized computer-vision requirements yields medium competition.
Core CV/ML skills transfer across industries but construction-specific data and BIM domain needs raise sensitivity to medium.
Explicit 4–8 years requirement plus mandatory CV/ML architectures and deployment experience implies high strictness.
Design, develop, and deploy AI-powered computer vision solutions to automate and augment construction workflows using diverse data sources like images, videos, drone imagery, LiDAR, and 3D data.
Build, optimize, and fine-tune advanced models (e.g., CNN, Vision Transformers, YOLO, Mask R-CNN) for tasks including object detection, segmentation, OCR, and video analytics in production environments.
Lead dataset engineering efforts including annotation strategy, data augmentation, synthetic data generation, and collaborate with AI Engineers, Data Scientists, and software teams for production-ready computer vision systems.
4–8 years of experience in Computer Vision with hands-on skills in AI/ML development and production deployment.
Proficiency in Python and deep learning frameworks with experience in CNNs, Vision Transformers, and foundation vision models.
Experience in building and optimizing models for object detection, segmentation, video analytics, OCR, and handling large-scale image/video datasets.
Work Experience Required: 4–8 years in Computer Vision; Notice period: Not explicitly mentioned in the JD.
Experienced Computer Vision Engineer with strong background in deploying scalable AI solutions in production, particularly in construction or engineering domains.
Proficient in advanced computer vision architectures and foundation models, comfortable working end-to-end from dataset design to deployment and model optimization.
Collaborative and able to work in Agile teams alongside AI engineers, data scientists, BIM experts, and software engineers on multi-disciplinary projects involving multimodal AI and visual intelligence.