Job Description

Job Requirements

Job Overview:


We are seeking a highly skilled AI Perception Engineer with a strong background in automotive software development to join our advanced driver assistance systems (ADAS) team. The ideal candidate will have hands-on experience in developing and optimizing perception algorithms using computer vision and deep learning techniques, especially CNNs and sensor fusion. You will play a key role in building intelligent systems that enable safer and smarter vehicles.


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Key Responsibilities:

Design, develop, and optimize AI-based perception algorithms for ADAS applications including object detection, classification, tracking, and segmentation. Work with multi-modal sensor data (camera, radar, LiDAR) and implement sensor fusion algorithms to enhance environmental perception. Train, validate, and deploy convolutional neural networks (CNNs) using real-world automotive datasets. Collaborate closely with systems engineering and feature teams to translate requirements into robust perception solutions. Implement algorithms in real-time embedded environments and ensure integration with automotive-grade operating systems. Support system-level design, calibration, and validation activities. Conduct root-cause analysis and performance tuning of perception systems. Document design, development processes, and participate in code reviews to ensure high software quality. Engage in cross-functional collaboration with ADAS feature development, safety, systems, and platform teams.

Work Experience

Required Qualifications:

Bachelor's or Master's degree in Computer Science, Electrical Engineering, Robotics, or a related field. 5+ years of hands-on experience in automotive software development, specifically in ADAS and AI perception. Strong experience in object detection, CNNs, deep learning frameworks (e.g., TensorFlow, PyTorch), and computer vision. Proficiency in programming languages such as C++, Python, and familiarity with embedded systems. Experience working with sensor data from camera, radar, and LiDAR; understanding of sensor fusion techniques. Solid understanding of operating systems, software architecture, and systems engineering principles. Demonstrated problem-solving and analytical thinking in complex technical environments. Excellent verbal and written communication skills; ability to clearly articulate technical issues and solutions.

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Preferred Qualifications:

Experience with real-time processing and deployment on automotive ECUs or SoCs (e.g., NVIDIA DRIVE, TI TDA, Qualcomm). Familiarity with automotive standards and processes: ISO 26262, ASPICE, AUTOSAR. Experience with dataset creation, annotation, and performance evaluation metrics for perception models. * Exposure to development tools such as ROS, OpenCV, MATLAB/Simulink, and Git.