Computer Vision Scientist
L&T Technology Services · Santa Clara, CA
Tailor my CV for this job — freeComputer Vision Scientist – L&T Group AI Center of Excellence
You will apply state-of-the-art 2D and 3D vision to high-impact problems such as quality inspection, construction progress monitoring, worker safety, and asset health, and own the CoE's reusable vision platform for Engineering, Manufacturing, Infrastructure, Energy, and Defence.What You'll DoDesign, train, and optimize models for detection, segmentation, tracking, pose estimation, and anomaly detection, including adapting foundation models (SAM, DINOv2, YOLO, ViT) to industrial and site imagery.Build 3D vision capabilities: depth estimation, point-cloud processing, photogrammetry, and scene reconstruction.Take solutions from proof of concept to production with clear business-value metrics, and integrate outputs with BIM, digital twins, and enterprise systems.Set data acquisition and labeling standards across camera, drone, thermal, and LiDAR sources; use synthetic and self-supervised methods to reduce annotation effort.Optimize models for real-time edge inference (NVIDIA Jetson, industrial cameras) with quantization, pruning, and TensorRT or OpenVINO; work with MLOps on monitoring and retraining.Mentor scientists and engineers, contribute to the CoE repository, and publish or file patents.First 12 MonthsDefine the CoE computer vision roadmap and reusable vision platform.Deliver 3–5 vision proofs of concept, at least 2 scaled to production.Establish a standard annotation and model evaluation framework, and publish an edge deployment reference architecture.What We're Looking ForMaster's or PhD in Computer Science, Electrical Engineering, AI, Applied Mathematics, or a related field (PhD preferred).8–15 years in computer vision and machine learning, with a track record of production deployments. Industrial, manufacturing, construction, or infrastructure experience is strongly preferred.Deep expertise in CNNs, vision transformers, and modern detection and segmentation architectures.Strong Python and C++, with PyTorch, OpenCV, and 3D libraries such as Open3D or PCL; hands-on video analytics and edge AI deployment. Publications at CVPR, ICCV, ECCV, NeurIPS, or similar venues are a plus.