ML engineer

Machine Learning Engineer

Location: Reading (Hybrid Preferred)

Salary: Up to £80k

Tech Stack: Python, PyTorch, Image-based ML, Anomaly Detection

Focus Areas: Optical/UV/Thermal Imaging, Sensor Data, Predictive Maintenance

Overview

We’re looking for a Machine Learning Engineer to lead the development of cutting-edge predictive maintenance models. You'll work with optical, UV, and thermal imaging data alongside environmental sensor data (pressure, temperature, humidity) to detect trends, predict failures, and enhance equipment reliability.

This is a high-impact role where you'll build deep learning models from scratch, leverage anomaly detection techniques, and explore synthetic data generation to improve real-world industrial systems.

Key Responsibilities

Develop & Deploy Machine Learning Models

• Build image-based ML models using Python & PyTorch for predictive maintenance
• Apply anomaly detection techniques to classify failures and improve system reliability
• Implement self-supervised learning methods to enhance detection accuracy

Work with Multimodal Data (Images + Sensors)

• Process and fuse optical, UV, and thermal imaging data with environmental sensor data
• Handle time-series data and optimize models for real-time insights

Optimize & Scale for Deployment

• Develop scalable, maintainable ML pipelines
• Deploy models using Docker and GPU acceleration for efficient inference
• Collaborate with hardware engineers to integrate ML solutions into high-voltage environments

Must-Have Skills & Experience

Python & PyTorch – Proven experience building deep learning models

Image-based ML – Worked with optical, UV, or thermal imaging data

Anomaly Detection & Predictive Maintenance – Strong understanding of failure classification, self-supervised learning, and synthetic data generation

ML Model Deployment – Experience setting up ML models from scratch & deploying in production

Multimodal Learning – Comfortable working with sensor data + images

Nice-to-Have Skills

Experience with high-voltage equipment or industrial robotics.

Hands-on with GPU-based model optimization & edge deployment.

Knowledge of transformers, CNNs, or spectrogram-based ML approaches.

Apply to hear more or send your CV to [email protected]