Machine Perception Engineer (Vision)

8+ years of experience in applied perception or computer vision. Proficiency in Python and deep learning frameworks (PyTorch or TensorFlow). Experience with model optimization techniques (pruning, quantization, TensorRT). Strong understanding of classical vision (OpenCV) and deep learning methods. Familiarity with maritime, aerospace, or harsh-environment sensing applications is a plus. Experience with sensor fusion, Kalman filtering, or multi-modal neural networks. Excellent problem-solving, debugging, and software design skills. Strong communication skills, ability to lead technical direction, and mentor junior engineers.

Lead design, training, and deployment of computer vision models for vessel detection, classification, and tracking. Architect and optimize inference pipelines for real-time performance on edge devices. Implement algorithms for scene understanding and object segmentation using image and sensor fusion data. Collaborate with hardware/software teams for model compatibility with embedded systems. Develop techniques for edge-case detection and self-healing model behavior. Apply active learning, domain adaptation, and synthetic data strategies. Integrate RF and sensor data into multimodal pipelines. Own model evaluation and benchmarking processes. Maintain best practices for model versioning and validation.