Perception Engineer

Key Responsibilities

• Develop and improve computer-vision capabilities including object detection, classification, multi-object tracking and false-alert reduction.
• Work with EO/IR and thermal imagery and, where useful, combine perception outputs with AIS, radar tracks and other system metadata.
• Build representative datasets, annotation practices, evaluation sets and repeatable performance benchmarks for field conditions.
• Analyse false positives, false negatives, dataset shift and operational failure modes, and translate findings into measurable improvements.
• Develop and evaluate multimodal AI, behaviour/event analytics and operator-assist functions where they provide clear operational value.
• Optimise and package models for practical edge deployment using ONNX, TensorRT / CUDA or equivalent, working with the Robotics Software Engineer.
• Support controlled experimentation with emerging techniques such as vision-language models, synthetic data and active learning, as well as integration tests and field trials.

Requirements

• Degree in Computer Science, Artificial Intelligence, Computer / Electrical Engineering, Robotics or a related discipline.
• Strong foundation in Python and practical machine-learning / computer-vision development; C++ capability would be advantageous.
• Hands-on experience in one or more of: object detection, tracking, image/video analytics, thermal imaging, multimodal AI or sensor fusion.
• Comfortable working with datasets, model evaluation, error analysis and quantitative performance metrics.
• Experience with PyTorch or equivalent, OpenCV, ONNX, TensorRT / CUDA, NVIDIA Jetson or edge deployment would be advantageous.
• Candidates with strong project, internship or practical engineering experience may also be considered; applied capability matters more than years of experience.