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.