Track This Job
Add this job to your tracking list to:
- Monitor application status and updates
- Change status (Applied, Interview, Offer, etc.)
- Add personal notes and comments
- Set reminders for follow-ups
- Track your entire application journey
Save This Job
Add this job to your saved collection to:
- Access easily from your saved jobs dashboard
- Review job details later without searching again
- Compare with other saved opportunities
- Keep a collection of interesting positions
- Receive notifications about saved jobs before they expire
AI-Powered Job Summary
Get a concise overview of key job requirements, responsibilities, and qualifications in seconds.
Pro Tip: Use this feature to quickly decide if a job matches your skills before reading the full description.
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.
- Experience using modern tooling (e.g., MLflow, Git, Airflow, Docker, Kubernetes, cloud environments).
- 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.
Location: Manchester, hybrid working.
Please note our client is unable to offer sponsorship for this opportunity. Finally, 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.
For similar roles, please reach out to Tom Parker, and follow Miryco Consultants - LinkedIn
Key Skills
Ranked by relevanceReady to apply?
Join Miryco Consultants Ltd and take your career to the next level!
Application takes less than 5 minutes

