Production ML Engineer — Hybrid, Growth & Impact

The Opportunity Hub UK Ltd; Newcastle; Hybride; AUD 90 000 - 126 000; Plein temps

Avantages offerts par ce poste

Salary £47k-£66k

Hybrid work

Private medical & dental

Enhanced pension & bonuses

Career development

Résumé du poste

The Opportunity Hub UK Ltd invites applications for a Machine Learning Engineer role in Newcastle. You will design, train, and validate production ML models and build scalable data pipelines feeding model training and inference.

You will work with data scientists and software engineers to move models from prototype to live deployment, monitor performance, and retrain when needed. Expect collaboration, code quality, and growth opportunities.

Qualifications

• Solid experience building and deploying machine learning models in production
• Strong Python skills and familiarity with ML frameworks
• Understanding of MLOps: versioning, CI/CD for models, monitoring
• Comfortable with cloud platforms (AWS, Azure, or GCP) and containerised deployments
• Good communication skills to explain model decisions
• Methodical debugging and curiosity about model behavior

Responsabilités

• Design, train and validate ML models for production use cases across the business
• Build and maintain data pipelines for model training and inference at scale
• Collaborate with data scientists and software engineers to move models from prototype to live deployment
• Monitor model performance in production and retrain or adjust when drift occurs
• Write clean, tested, documented code for ongoing maintainability
• Contribute to tooling, architecture, and best practices as the team grows

Connaissances

Production ML deployment

Python

MLOps

CI/CD for models

Model monitoring

Communication

Debugging

Formation

Bachelor's degree or equivalent

Outils

PyTorch

TensorFlow

scikit-learn

Description du poste

The Opportunity Hub UK Ltd invites applications for a Machine Learning Engineer role in Newcastle. You will design, train, and validate production ML models and build scalable data pipelines feeding model training and inference.

You will work with data scientists and software engineers to move models from prototype to live deployment, monitor performance, and retrain when needed. Expect collaboration, code quality, and growth opportunities.