ML Engineer (Computer Vision)

Machine Learning Engineer – Computer Vision Role Overview Develop and improve computer vision models across classification, object detection, segmentation, pose estimation and action recognition. The role focuses primarily on fine-tuning existing models, with opportunities to develop new models and automate training workflows. Responsibilities • Train, fine-tune and evaluate models to improve accuracy, robustness and efficiency. • Compare model architectures and explain their strengths, limitations and trade-offs. • Analyse model performance, investigate failure cases and test improvements. • Develop MLOps workflows and write or modify Python scripts to automate model training. Requirements • Degree in Computer Science, AI, Data Science or a related field. • At least two years of hands-on computer vision experience, including academic projects, internships or professional work. • Strong expertise in object detection, segmentation, pose estimation and action recognition • Proficiency in Python and PyTorch and/or TensorFlow. • Ability to explain model selection, training decisions and evaluation results. • Familiarity with Linux, Git and reproducible experimentation. Preferred • Experience modifying model architectures, heads, loss functions or training pipelines. • Exposure to MLOps, experiment tracking and model optimisation.