MLOps Engineer — Production ML, Databricks & CI/CD

Rock Entertainment Group; Greater London; Hybrid; GBP 90,000 - 120,000; Full time

Benefits offered by this job

Free gym membership

Hybrid working

Flexible culture

Private healthcare

Life insurance

Pension plan

25 days leave

Additional holiday

Learning resources

Enhanced family leave

Job summary

The PureGym Group is seeking a Machine Learning Engineer to join the Data and Analytics Team in a hybrid London role. You will drive models from notebook to reliable production services, owning deployment, monitoring and retraining while building reusable components and standards.

You will work with Data Scientists and Data Engineers to shape MLOps, bring software engineering practices into the modelling lifecycle, and accelerate production quality ML across PureGym businesses.

Qualifications

• Production experience with machine learning models in production.
• Strong Python and SQL with solid software engineering practices.
• Experience with MLflow or similar lifecycle tooling.
• Experience building CI/CD pipelines (GitHub Actions or Azure DevOps).

Responsibilities

• Own the path to production for ML models including packaging and deployment.
• Build robust CI/CD pipelines for models and data science code.
• Monitor data drift and model performance with alerts.
• Automate retraining and recurring model runs.
• Collaborate with Data Scientists and Data Engineers on model design.
• Define MLOps standards and model registry practices.
• Review code and mentor Data Scientists on software engineering.
• Monitor cost and performance of the model estate.

Skills

Python

SQL

Software testing

Code review

Version control

CI/CD

MLflow

GitHub Actions

Azure DevOps

Communication

Education

Computing/Engineering degree

Tools

MLflow

GitHub Actions

Azure DevOps

Databricks

Job description

The PureGym Group is seeking a Machine Learning Engineer to join the Data and Analytics Team in a hybrid London role. You will drive models from notebook to reliable production services, owning deployment, monitoring and retraining while building reusable components and standards.

You will work with Data Scientists and Data Engineers to shape MLOps, bring software engineering practices into the modelling lifecycle, and accelerate production quality ML across PureGym businesses.