Job Summary
This role focuses on the architectural development of visual SLAM (vSLAM) systems for high-resolution multi-camera setups, enhancing visual feature extraction and association, and applying advanced computational techniques to achieve real-time performance. You'll be instrumental in sensor fusion, data integrity analysis, and performance validation, driving high-quality solutions at the forefront of computer vision, robotics, and optimization.

Key Responsibilities

• Design and develop vSLAM architecture for multi-camera, high-resolution environments.
• Optimize visual feature extraction processes across multiple camera inputs.
• Implement CUDA and Tensor Core optimization techniques to accelerate vSLAM processing.
• Develop advanced algorithms to analyze and validate data integrity from sensors such as IMU and Encoders.
• Optimize controller hardware to enhance overall system performance, ensuring stability and efficiency.
• Continuously refine vSLAM algorithms to improve efficiency, speed, and scalability, ensuring alignment with real-time system requirements.
• Create logical test plans and data collection strategies to evaluate vSLAM performance against defined goals and key metrics, ensuring system robustness.

Required Qualifications

• Master's or Ph.D. in Electrical, Mechanical, Computer Engineering, or a related discipline, with over five years of industry experience.
• Strong proficiency in C++ with significant experience in scripting languages like Python.
• Deep expertise in 3D computer vision, multi-view geometry, and SfM/SLAM.
• Experience with CUDA and Tensor Core optimization for GPU performance.
• Knowledge of sensor calibration, data synchronization, and handling multi-sensor data.
• Solid mathematical foundation in multi-view geometry, linear algebra, and optimization.
• Familiarity with open-source optimization libraries like g2o, GTSAM, and Ceres.
• Proficiency in numerical linear algebra, probabilistic estimation, sensor fusion, and optimization techniques.
• Experience in debugging, profiling, and optimizing code for performance on both CPUs and GPUs.

Interested candidates, who wish to apply for the advertised position, please email us an updated copy of your resume.

We regret that only shortlisted candidates will be notified.

EA License No.: 01C4394

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