MLOps Engineer

Location: Hybrid role based in Leicester, Bexhill or London, United Kingdom. Sponsorship is not available.

Company

hirify.global is a digital insurance provider developing technology, pricing, data and analytics capabilities for the UK market.

What you will do

• Build, improve and maintain machine learning pipelines for Market Pricing.
• Productionise Python-based models, notebooks and data science workflows.
• Move models from development into repeatable, tested and documented production processes.
• Improve workflow testing, release, monitoring, versioning and maintenance.
• Investigate data, model and pipeline issues and automate manual steps where this improves quality, speed or control.
• Collaborate with Pricing, Data Science, Data Engineering, ML Engineering and governance stakeholders while ensuring traceability, auditability and safe change.

Requirements

• Strong Python skills and experience building data or machine learning workflows.
• Good SQL skills and confidence working with structured datasets.
• Experience building reliable, reusable and maintainable code or pipelines.
• Understanding of machine learning fundamentals, especially supervised learning.
• Experience with Git, code review, testing and technical documentation.
• Exposure to cloud-based data or engineering environments.
• Good problem-solving skills, attention to detail and clear communication with technical and non-technical audiences.
• Ability to work with data scientists, analysts, engineers and business stakeholders, with a practical focus on quality, reliability, governance and maintainability.

Nice to have

• Hands-on experience with Azure, AWS or GCP.
• Exposure to Snowflake, Databricks, Spark or similar data platforms.
• Experience with MLOps practices including model deployment, monitoring, versioning or model registries.
• Exposure to Airflow, MLflow, Azure DevOps, GitHub Actions or similar workflow and deployment tools.
• Experience in pricing, insurance, financial services or another regulated environment.
• Understanding of model governance, responsible AI or explainability.

Culture & Benefits

• Flexible hybrid working approach.
• Annual 4Cs performance bonus, matched pension contributions up to 10%, life assurance and income protection.
• 25 days of annual leave plus bank holidays, with an option to buy or sell one week.
• Health, dental, mental wellbeing and financial wellbeing support, including a 24/7 assistance programme.
• Training and development support, technology and cycle-to-work schemes, discounts and onsite facilities.
• Employment includes a thorough referencing process with credit and criminal record checks.

Hiring process

• Recruiter screening call followed by an introductory meeting with the hiring manager.
• Hiring team interview with a case study, followed by a final discussion with a business leader.