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• Design, implement, and validate multi‑modal sensor fusion algorithms (camera, depth, LiDAR, radar, IMU) for precise length/dimension measurement. • Build and maintain calibration pipelines, synchronized data capture/annotation, and quantitative evaluation metrics (e.g., RMS error, latency, robustness). • Integrate and optimize models for target hardware; perform lab and field verification/validation with SW/systems/manufacturing teams. • Develop and validate state-of-the-art AI/ML for 3D perception (reconstruction, object detection, segmentation, keypoint detection, dense depth estimation) to support high-precision measurement tasks. • Design and operate part measurement testbeds (fixtures, jigs, lighting, data logging) and integrate standard metrology devices.

• Master’s degree in Robotics, Electrical Engineering, Computer Science with minimum 3 years of relevant work or research experience or Ph.D degree in a relevant field. • Expertise in designing and implementing advanced AI algorithms for high-precision length and dimension measurement using multi-modal sensor fusion. • Demonstrate experience implementing AI/ML solutions for detection, segmentation, depth, or 3D reconstruction with production‑level validation. • Hands‑on experience with camera and LiDAR calibration, synchronized multi‑sensor data collection, and implementation of CV/ML algorithms for 3D perception or precision measurement. • Hands-on experience designing and operating experimental measurement setups (fixtures, lighting, jigs) and using industrial metrology tools (e.g., CMM, high-precision gauges) for resolution and accuracy verification. Solid understanding of multi‑view geometry and probabilistic state estimation (e.g., Kalman filters). Proficiency in Python and ML/CV frameworks (e.g., PyTorch/TensorFlow, OpenCV).

• Ph.D. degree with minimum two years of work experience in Robotics, Electrical Engineering, Computer Science. • Experience integrating radar and IMUs, sensor time‑synchronization, and latency compensation. • In-depth knowledge of AI-based Multi-Level Fusion (early, feature, and late-level) with projection-based (e.g., PointPainting), transformer-based (e.g., FUTR3D), and hybrid models. • Familiarity with ROS, PCL, CI/CD for ML, and hardware‑in‑the‑loop validation in industrial/manufacturing settings

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