Hybrid ML Engineer — Production AI & Cloud

SPG Resourcing; Warrington; Hybrid; GBP 55,000 - 85,000; Full time

Job summary

SPG Resourcing, on behalf of a financial services organisation, is recruiting a Machine Learning Engineer for a hybrid role. You will contribute to a cross-functional data team, taking ML models from research to production and delivering scalable AI solutions.

The role emphasizes designing end-to-end ML workflows, CI/CD, IaC, and collaboration with Data Scientists, Data Engineers and Software Engineers to deploy robust ML systems in a cloud environment.

Qualifications

• Commercial experience in ML Engineering or Data Science within a production environment
• Strong Python development skills with solid software engineering practices
• Experience deploying ML solutions into cloud-native production environments
• Experience with Docker and Kubernetes in production
• Knowledge of CI/CD, Git and IaC
• Experience with Azure and Databricks is beneficial

Responsibilities

• Design and enhance the organisation's ML engineering capability and Data Science platform
• Build and automate end-to-end ML workflows with CI/CD and Infrastructure as Code
• Collaborate with Data Scientists throughout model development and deployment
• Deliver production-ready AI solutions with engineering standards
• Develop high-quality Python code following best practices
• Contribute to deployment strategies and solution architecture
• Support deployment and operationalisation of ML and Generative AI solutions
• Grow the engineering function with tooling and best practices

Skills

Python

ML Engineering

Cloud deployments

CI/CD

Kubernetes

Docker

MLOps

Agile

Communication

Git

Education

Bachelor's degree in a relevant field

Tools

Azure

Databricks

Jira

Job description

SPG Resourcing, on behalf of a financial services organisation, is recruiting a Machine Learning Engineer for a hybrid role. You will contribute to a cross-functional data team, taking ML models from research to production and delivering scalable AI solutions.

The role emphasizes designing end-to-end ML workflows, CI/CD, IaC, and collaboration with Data Scientists, Data Engineers and Software Engineers to deploy robust ML systems in a cloud environment.