Machine Learning Engineer — Computer Vision, Deploy Real‑World CV

Platform Recruitment; Greater London; On-site; GBP 96,000 - 160,000; Full time

Job summary

Platform Recruitment in London is seeking a Machine Learning Engineer to design, train and deploy computer vision models, building production-ready systems and driving ML projects from research to deployment.

You will work with engineers, data scientists and domain experts across the lifecycle, handling real-world datasets, evaluating models and contributing to technical decisions across projects.

Qualifications

• Degree from a Russell Group university in Computer Science, Mathematics, Engineering, Physics, or a related discipline
• At least 2 years of commercial experience in a Machine Learning, AI, or Computer Vision Engineering role
• Strong Python programming skills
• Experience with PyTorch, TensorFlow, or similar machine learning frameworks
• Experience developing computer vision models using techniques such as object detection, image classification, segmentation, or tracking
• Experience working with real-world datasets and deploying models into production environments
• Strong communication skills and the ability to work within a multidisciplinary team

Responsibilities

• Design, train, and deploy computer vision models across the full ML lifecycle
• Build production-ready systems and evaluate model performance
• Contribute to technical decisions across multiple projects

Skills

Communication

Multidisciplinary teamwork

Research to deployment

Education

Russell Group degree in CS/Math/Engineering/Physics

Tools

Python

PyTorch

TensorFlow

Computer Vision

Job description

Platform Recruitment in London is seeking a Machine Learning Engineer to design, train and deploy computer vision models, building production-ready systems and driving ML projects from research to deployment.

You will work with engineers, data scientists and domain experts across the lifecycle, handling real-world datasets, evaluating models and contributing to technical decisions across projects.