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.