Machine Learning Specialist

MLOps Engineer

York | Hybrid

Salary: Up to £60,000 (adjustable depending on experience)

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 continues to invest in modern cloud, data and machine learning capabilities.

You’ll join a growing technology function where you’ll have the opportunity to develop your technical skills, work with experienced colleagues and contribute to the delivery of innovative machine learning solutions.

The Role

We’re looking for a motivated Machine Learning Engineer to help develop, deploy and maintain machine learning solutions in production. Working closely with Data Scientists, Data Engineers and Platform Engineers, you’ll support the infrastructure, APIs and deployment pipelines that enable models to move from development into live environments.

This is an excellent opportunity for someone with a foundation in Python development, cloud technologies and machine learning who wants to build their experience in MLOps, automation and production engineering.

Key Responsibilities

• Support the deployment and maintenance of machine learning models in batch and real-time environments.
• Develop and maintain Python APIs using frameworks such as Flask or FastAPI.
• Help build and improve CI/CD pipelines for model deployment.
• Contribute to automating model training, testing, deployment and monitoring processes.
• Assist with maintaining model registries, versioning and monitoring solutions.
• Support the development of reliable cloud-based machine learning services.
• Write clean, maintainable and well-tested Python code.
• Use Git and follow good software engineering practices, including code reviews and automated testing.
• Work with Terraform or similar tools to manage cloud infrastructure.
• Help monitor model performance, investigate issues and improve service reliability.
• Collaborate with Data Scientists and Data Engineers to productionise machine learning models.
• Contribute ideas for improving existing MLOps processes, tooling and ways of working.

Qualifications & Skills

Required

• A degree in Computer Science, Data Science, Mathematics, Engineering or another relevant discipline, or equivalent practical experience.
• Around 1–3 years’ experience in software engineering, machine learning engineering, data engineering or a related technical role.
• Good Python programming skills and an understanding of software development principles.
• A basic understanding of machine learning concepts and the process of deploying models into production.
• Some experience developing APIs, ideally using Flask, FastAPI or similar frameworks.
• Familiarity with Git, CI/CD pipelines and automated testing.
• Exposure to cloud platforms such as Azure, AWS or GCP.
• Familiarity with Docker and containerised applications.
• An understanding of infrastructure automation, ideally using Terraform or similar tools.
• An interest in monitoring, logging, model performance and production support.
• Strong problem-solving skills, a willingness to learn and the ability to work collaboratively.

Preferred

• Experience supporting the deployment of machine learning models or data science applications.
• Exposure to MLOps tools, model registries or experiment tracking platforms.
• Experience working with data scientists or data engineering teams.
• Familiarity with Agile development practices and collaborative software engineering.
• An interest in financial services or other regulated industries.
• Exposure to cloud-based data platforms and scalable data processing environments.

Benefits

• Competitive salary and performance-related bonus.
• Employer pension contribution.
• Health and wellbeing benefits.
• Generous annual leave.
• Flexible and hybrid working.
• Professional development and training opportunities.
• Exposure to modern cloud, data and machine learning technologies.
• Support from experienced colleagues and opportunities to develop your MLOps expertise.
• The opportunity to contribute to the growth of the organisation’s machine learning capabilities.

Equal Opportunity Statement

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