Vision & Perception AI Engineer
Key Skills for This Role
Full Job Posting
Design, develop, optimize, and deploy computer vision and perception AI solutions across automotive cabin intelligence, smart surveillance, industrial IoT, and factory inspection applications. Develop end-to-end perception pipelines for object detection, tracking, segmentation, activity recognition, anomaly detection, and visual reasoning using state-of-the-art CNN and transformer-based architectures.
Key Responsibilities
- Develop and optimise perception models for automotive, surveillance, industrial inspection, and edge AI applications.
- Build AI solutions for factory automation, quality inspection, defect detection, worker safety monitoring, and process compliance.
- Design and deploy multi-camera video analytics systems for smart surveillance and IoT use cases.
- Train, fine-tune, and optimise deep learning models for edge and cloud deployment.
- Collaborate with platform, embedded, and AI teams to deploy solutions on automotive SoCs, edge AI accelerators, and GPU platforms.
Required Technical Skills
- Strong understanding of Computer Vision and Deep Learning fundamentals.
- Hands-on experience with CNN-based architectures including:
- YOLOv5, YOLOv7, YOLOv8, YOLOX
- PP-YOLOE
- EfficientDet
- Faster R-CNN
- Mask R-CNN
- SSD
- RetinaNet
- Experience with image classification, object detection, semantic/instance segmentation, pose estimation, and multi-object tracking.
- Experience with PyTorch, TensorFlow, ONNX, TensorRT, OpenVINO, or equivalent optimisation frameworks.
- Familiarity with edge AI deployment on NVIDIA, Qualcomm, Intel, or similar platforms.
- Knowledge of multimodal AI, Vision-Language Models (VLMs), and perception systems is a plus.
Preferred Domain Experience
- Automotive Cabin AI and Occupant Monitoring
- Smart Surveillance and Video Analytics
- Factory Inspection and Industrial Automation
- Smart Cities and Edge AI IoT Solutions
- Retail Analytics and Operational Intelligence
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