Machine Perception Engineer (Vision)

Bachelors, Master’s or PhD in Computer Vision, Machine Learning, Robotics, or related field. 8+ years of experience in applied perception or computer vision, in performance critical applications Proficiency in Python and deep learning frameworks such as PyTorch or TensorFlow. Experience with model optimization techniques such as pruning, quantization, or TensorRT deployment. Strong understanding of classical vision (OpenCV) as well as modern deep learning methods. Familiarity with maritime, aerospace, or other harsh-environment sensing applications is a strong plus. Experience with sensor fusion, Kalman filtering, or multi-modal neural networks. Excellent problem-solving, debugging, and software design skills. Strong communication skills, with the ability to lead technical direction and mentor junior engineers.

Lead design, training, and deployment of computer vision and perception models. Architect and optimize inference pipelines for real-time edge device performance. Implement algorithms for scene understanding, object segmentation, and environmental awareness. Collaborate with hardware and software teams for model compatibility. Develop techniques for edge-case detection, dataset curation, and self-healing models. Apply active learning, domain adaptation, and synthetic data strategies. Integrate complementary sensor data into multimodal pipelines. Own model evaluation processes and benchmarking. Maintain best practices for model versioning, traceability, and validation.