Machine Learning Engineer - Financial Services

Miryco Consultants Ltd; Manchester; On-site; GBP 65,000 - 90,000; Full time

Job summary

A financial services business in Manchester is seeking a Machine Learning Engineer to build and maintain ML tooling and deployment frameworks. The role emphasizes collaborative work with data teams and the importance of engineering best practices. Ideal candidates have strong Python skills and experience in data science or ML Ops, particularly in financial services. The position offers a competitive salary plus bonus.

Qualifications

• Strong Python engineering skills in a data science or ML Ops environment.
• Ability to create scalable, maintainable, production-ready solutions.
• Experience in financial services, regulated environments, or analytical delivery is beneficial.
• Experience in financial services or regulated environments is a plus.

Responsibilities

• Build and maintain ML tooling and deployment frameworks.
• Develop scalable Python-based solutions and monitoring tools.
• Champion ML engineering best practices including CI/CD principles.
• Collaborate with data scientists, product, and engineering teams.
• Support ML governance and model lifecycle management.

Skills

Python engineering skills

Ability to translate analytical work into engineering solutions

Collaborative mindset

Job description

Machine Learning Engineer - Financial Services

Join a growing financial services business undergoing an exciting modernisation of its data, analytics, and machine learning capability. With significant investment across technology, tooling, and engineering standards, this is a role where you’ll shape ML engineering foundations and help accelerate end-to-end analytical delivery.

You’ll work in a high-impact environment where ML capability directly influences customer outcomes, pricing, risk, personalisation, and operational efficiency. If you’re motivated by engineering excellence, autonomy, and the chance to build scalable frameworks others rely on — this is a compelling next step.

What you’ll do

• Build and maintain ML tooling, packages, and deployment frameworks to streamline and standardise modelling workflows.
• Develop scalable Python-based solutions, model evaluation metrics, and monitoring tooling to ensure operational stability and continuous improvement.
• Champion ML engineering best practice — including CI/CD principles, testing frameworks, reproducibility, and automation.
• Work cross‑functionally with data scientists, product, and engineering teams to ensure models can be deployed, monitored, and iterated with confidence.
• Support the development of ML governance, model lifecycle management, and performance tracking processes.

About you

• Strong Python engineering skills applied in a commercial data science or ML Ops environment.
• Ability to translate analytical work into scalable, maintainable, production‑ready engineering solutions.
• Collaborative mindset — able to work effectively with both technical and non‑technical teams.
• Experience in financial services, regulated environments, or large‑scale analytical delivery is beneficial.

Salary

Competitive base salary plus bonus.

Please note our client is unable to offer sponsorship for this opportunity. Should you not be contacted within five working days of submitting your application, then unfortunately you have not been shortlisted for the opportunity. We will however be in touch should there be any other opportunities of potential interest that are suiting to your skills.