Build scalable infrastructure for machine learning training, deployment, monitoring, retraining, and continual learning. Responsibilities include distributed training pipelines, dataset and annotation workflows, experiment tracking, model versioning, benchmarking, CI/CD, cloud-to-edge deployment, inference APIs, and embedded NVIDIA platform optimization. The role collaborates with computer vision, navigation, embedded software, and cloud engineering teams to move AI research into reliable production systems.

Develop advanced 3D computer vision and spatial AI systems for wearable construction technology. Build scene understanding, segmentation, object detection, BIM correspondence, localization, and installation-progress models using multimodal sensor data. Design and train deep learning systems, optimize inference for NVIDIA Jetson using TensorRT, CUDA, and ONNX, and deploy robust production pipelines. Contribute to architecture and R&D strategy while mentoring engineers and collaborating across navigation, embedded software, hardware, and product teams.