The posting
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.



