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.