Machine Learning Engineer

Fruition Group; England; Hybrid; GBP 65,000 - 85,000; Full time

Job summary

A leading technology company is seeking a Machine Learning Engineer - Computer Vision to lead the development of models that detect damage on large vehicles. This role involves designing and optimizing object detection models, collaborating with various teams, and ensuring operational success of ML systems. Candidates should have significant machine learning experience, particularly in computer vision and proficiency in Python. The position offers a salary of £65,000 - £85,000 and comes with opportunities for growth and impact.

Qualifications

• Strong experience in machine learning focused on computer vision.
• Hands‑on experience training and deploying object detection or segmentation models such as YOLO.
• Ability to translate operational or business problems into measurable ML objectives.

Responsibilities

• Design, train and optimise computer vision models for vehicle damage detection.
• Improve model accuracy, precision and recall across priority damage categories.
• Collaborate with MLOps and platform teams to package, deploy and monitor models.

Skills

Machine learning

Computer vision

Python

Object detection

Segmentation models

Job description

Job Title: Machine Learning Engineer - Computer Vision

Location: UK Remote/Hybrid

Salary: £65,000 - £85,000 plus benefits

Why Apply?

This is a chance to take ownership of a clearly defined machine learning problem space within a growing technology environment focused on real‑world AI applications. You will lead the development of computer vision models used to detect damage on large commercial vehicles, working with complex imagery, challenging angles, and highly variable real‑world data. The role offers genuine ownership, fast iteration cycles, and the opportunity to see your models deployed into operational use rather than remaining in research.

Responsibilities

• Design, train and optimise computer vision models for vehicle damage detection using object detection and segmentation approaches
• Improve model accuracy, precision and recall across priority damage categories through structured evaluation and retraining
• Work closely with data and annotation teams to define damage classes, identify data gaps and address class imbalance
• Carry out error analysis to understand false positives and negatives and drive targeted model improvements
• Own evaluation datasets, metrics and performance reporting across training, validation and test sets
• Collaborate with MLOps and platform teams to package, deploy and monitor models in production
• Identify performance issues such as data drift and support rollout of inspection capability to additional locations

Requirements

• Strong experience in machine learning focused on computer vision
• Hands‑on experience training and deploying object detection or segmentation models such as YOLO or similar architectures
• Proficiency in Python and common ML and computer vision libraries
• Experience working with large image datasets and noisy real‑world data
• Ability to translate operational or business problems into measurable ML objectives
• Comfortable working in an iterative, delivery‑focused engineering environment

What's in it for me?

• Ownership of an end‑to‑end ML problem with real operational impact
• Opportunity to build and scale production computer vision systems
• Work with cross‑functional teams spanning data, operations and platform engineering
• Exposure to complex, real‑world datasets rather than synthetic or lab‑only use cases
• Long‑term growth as part of an expanding AI capability

We are an equal opportunities employer and welcome applications from all suitably qualified persons regardless of their race, sex, disability, religion or belief, sexual orientation or age.