ML Ops Engineer

SPG Resourcing; York and North Yorkshire; On-site; GBP 68,000 - 83,000; Full time

Benefits offered by this job

Competitive salary

Annual bonus

Pension contribution

Health benefits

Generous annual leave

Professional development

Modern cloud tech

Collaborative culture

Job summary

SPG Resourcing is seeking an experienced Machine Learning Engineer in the United Kingdom to design, deploy and scale production‑grade ML solutions. You will build infrastructure, APIs and deployment pipelines supporting the full ML lifecycle, collaborating with Data Scientists, Data Engineers and Platform Engineers.

The role focuses on MLOps, real‑time and batch deployments, cloud services and a strong emphasis on software engineering, testing and Agile delivery.

Qualifications

• 3–5 years’ experience in machine learning engineering or a related role.
• Experience deploying and supporting ML models in production.
• Good understanding of machine learning and data science principles.
• Experience with APIs, preferably Flask or FastAPI.
• Strong software engineering and testing practices.
• Experience with TDD, Git and CI/CD.
• Experience with Terraform or similar Infrastructure as Code tools.
• Hands‑on experience with Azure, AWS or GCP.
• Familiarity with Docker and containerised deployments.
• Understanding of monitoring, logging and API operations.
• Strong problem‑solving and communication skills.
• Experience working in Agile teams.

Responsibilities

• Build and maintain infrastructure for real‑time and batch ML model deployment.
• Develop Python APIs using Flask, FastAPI or similar frameworks.
• Design and maintain CI/CD pipelines for ML deployment.
• Automate the ML lifecycle, including data preparation, training, evaluation, deployment and monitoring.
• Develop and maintain model registries and monitoring solutions.
• Build reliable, scalable cloud‑based ML services.
• Write high‑quality, tested and maintainable Python code.
• Apply software engineering, TDD and Agile best practices.
• Collaborate with Data Scientists, Data Engineers and Platform Engineers.
• Monitor and improve the performance, reliability and security of ML services.
• Help mature the organisation’s data science and MLOps capabilities.

Skills

Python

Flask/FastAPI

CI/CD

Terraform

Cloud platforms

Docker

MLOps

Testing

Agile

API development

Tools

Flask

FastAPI

Docker

Terraform

Azure

AWS

GCP

Job description

Salary: Up to £75,000 + 15% Annual Bonus

Company Overview

Join a leading international organisation with an ambitious technology and data strategy. The organisation combines a strong commercial focus with a collaborative, inclusive culture and invests in modern cloud, data and machine learning capabilities. You’ll join a growing technology function where innovation, ownership and continuous improvement are encouraged.

The Role

We’re looking for an experienced Machine Learning Engineer to help build and scale production‑grade machine learning solutions. You’ll develop the infrastructure, APIs and deployment pipelines that support the full ML lifecycle, working closely with Data Scientists, Data Engineers and Platform Engineers. This is a hands‑on role with the opportunity to shape MLOps practices and the organisation’s growing machine learning capability.

Key Responsibilities

• Build and maintain infrastructure for real‑time and batch ML model deployment.
• Develop Python APIs using Flask, FastAPI or similar frameworks.
• Design and maintain CI/CD pipelines for ML deployment.
• Automate the ML lifecycle, including data preparation, training, evaluation, deployment and monitoring.
• Develop and maintain model registries and monitoring solutions.
• Build reliable, scalable cloud‑based ML services.
• Write high‑quality, tested and maintainable Python code.
• Apply software engineering, TDD and Agile best practices.
• Collaborate with Data Scientists, Data Engineers and Platform Engineers.
• Monitor and improve the performance, reliability and security of ML services.
• Help mature the organisation’s data science and MLOps capabilities.

Qualifications & Skills

Required

• 3–5 years’ experience in machine learning engineering or a related role.
• Experience deploying and supporting ML models in production.
• Good understanding of machine learning and data science principles.
• Experience with APIs, preferably Flask or FastAPI.
• Strong software engineering and testing practices.
• Experience with TDD, Git and CI/CD.
• Experience with Terraform or similar Infrastructure as Code tools.
• Hands‑on experience with Azure, AWS or GCP.
• Familiarity with Docker and containerised deployments.
• Understanding of monitoring, logging and API operations.
• Strong problem‑solving and communication skills.
• Experience working in Agile teams.

Preferred

• Experience in financial services, insurance or another regulated industry.
• Experience with MLOps platforms and tooling.
• Experience working across multiple cloud platforms.
• Experience taking data science models from development into production.
• Competitive salary and performance‑related bonus.
• Employer pension contribution.
• Health and wellbeing benefits.
• Generous annual leave.
• Professional development and training opportunities.
• Exposure to modern cloud, data and machine learning technologies.
• Collaborative environment with opportunities to influence and shape ML engineering practices.

Equal Opportunity Statement

We are an equal opportunities employer and are committed to fostering an inclusive workplace which values and benefits from the diversity of the workforce we hire. We offer reasonable accommodation at every stage of the application and interview process.