Automotive AI Perception Engineer ADAS

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.

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 or Master 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.

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.