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Mid-level metro role but niche robotics perception reduces broad applicant pool.
Highly domain-specific robotics perception skills make cross-industry transfers difficult.
Mandatory 5+ years, C++/PyTorch, SLAM and sensor expertise enforce moderate filtering.
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Develop and deploy realtime 3D perception pipelines using LiDAR, IMU, Stereo, and RGB cameras for robotic construction applications.
Design and optimize algorithms for semantic scene understanding, ego-motion estimation, localization, and sensor fusion combining classical and deep learning methods.
Lead calibration procedures development, automate online drift detection and maintain perception KPIs integrating outputs with navigation, manipulation, and cloud systems.
5+ years of work experience in computer vision and 3D perception or related fields.
Strong fundamentals in computer vision and 3D perception with proficiency in C++; Python and frameworks like PyTorch are a plus.
Familiarity with localization and SLAM techniques and ability to handle and debug real-world sensor data.
Not explicitly mentioned in the JD: specific degree requirement, notice period, or mandatory onsite location.
Experienced engineer comfortable working at the intersection of classical perception algorithms and deep learning in robotics environments.
Capable of handling complex sensor fusion, calibration, and optimization for resource constrained edge devices.
Practitioner familiar with real-world robotic systems deployed in dynamic and unstructured environments, preferably with hands-on experience in construction robotics or similar sectors.