Purpose of the Job:Contribute to the development, testing, and optimization of perception algorithms for Brightskies’s Level 3 and Level 4 autonomous driving systems, with strong hands-on coding skills in C++ and Python for multi-sensor environmental perception.
Responsibilities and Duties:Develop and refine algorithms for 2D/3D object detection, classification, tracking, and segmentation using LiDAR, camera, radar, and ultrasonic data. Implement multi-sensor fusion methods. Assist in the integration of perception models into real-time embedded processing pipelines. Perform model training, evaluation, and optimization to improve accuracy and efficiency. Contribute to sensor calibration and synchronization procedures. Execute perception modules in both simulation and real-world environments, logging and analyzing results. Conduct data preprocessing, cleaning, and annotation validation for model development. Apply model optimization techniques such as quantization and Tensor RT deployment. Participate in code reviews, debugging, and CI/CD pipeline integration. Keep up to date with perception-related research, frameworks, and tools.
Education:Bachelor’s degree in Computer Science, Electrical Engineering, Robotics, or a related field.
Experience:0–3 years of experience in computer vision, perception, or machine learning Proficiency in both C++ (modern standards) and Python for algorithm implementation and integration. Solid understanding of LiDAR, camera, radar, and ultrasonic sensor data formats and processing methods. Hands-on experience with deep learning frameworks (Tensor Flow, PyTorch) for perception tasks. Familiarity with ROS / ROS2 and real-time system constraints. Knowledge of probabilistic state estimation (e.g., Kalman filters) and basic tracking algorithms. Experience working with datasets for perception model training and validation. Additional:Proficient with Git, Linux development environments, and Agile workflows. Familiarity with GStreamer or similar high-throughput streaming frameworks is a plus. Exposure to embedded deployment workflows and GPU acceleration is an advantage. Strong interest in autonomous vehicle technology and real-time robotics applications. Skills and Abilities:
Programming: C++17/20, Python 3.x (strong coding ability required) Frameworks & Libraries: ROS, ROS2, Tensor Flow, PyTorch, Open CV, PCLSensors: LiDAR, camera, radar, ultrasonic Optimization Tools: Tensor RT, CUDA (basic usage) Version Control: Git, Git Lab/Git Hub Soft Skills: Problem-solving, adaptability, attention to detail, ability to work in a collaborative team