MLOps Engineer

Jobtailor; Leicester; On-site; GBP 55,000 - 85,000; Full time

Job summary

Jobtailor is seeking a skilled MLOps engineer to build, productionise and maintain ML pipelines in a Market Pricing context. The role emphasizes Python workflows, data engineering collaboration and governance across data science and pricing teams.

You will own MLOps components, improve testing and monitoring, and work with stakeholders to ensure auditable and safe production of models.

Qualifications

• 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 and attention to detail.
• Clear communication skills and ability to explain technical ideas to different audiences.
• Comfortable working with data scientists, analysts, engineers and business stakeholders.
• Practical focus on quality, reliability, governance and maintainability.
• Hands-on experience with Azure, AWS or GCP is nice to have.
• Exposure to Snowflake, Databricks, Spark or similar is nice to have.
• Experience with MLOps practices is nice to have.
• Exposure to Airflow, MLflow, Azure DevOps, GitHub Actions or similar is nice to have.
• Experience in pricing, insurance, financial services or another regulated environment is nice to have.
• Understanding of model governance, responsible AI or explainability is nice to have.
• Sponsorship is unavailable for this position.
• Successful applicants undergo credit and criminal record checks.

Responsibilities

• Build, improve and maintain machine learning pipelines used within Market Pricing.
• Productionise Python-based models, notebooks and data science workflows.
• Move models from development into repeatable, tested and documented production processes.
• Improve testing, release, monitoring and maintenance of model workflows.
• Investigate issues across data, model and pipeline workflows.
• Automate manual steps to improve quality, speed or control.
• Support Git, code review, testing and documentation practices.
• Ensure pipelines and model workflows are traceable, auditable and safe to change.
• Collaborate with Pricing, Data Science, Data Engineering, ML Engineering and governance stakeholders.
• Own defined MLOps components and pipelines.
• Work with senior colleagues on standards, architecture and governance.

Skills

Python programming

SQL proficiency

Problem solving

Attention to detail

Clear communication

Stakeholder collaboration

Quality governance

Tools

Azure

AWS

GCP

Snowflake

Databricks

Spark

Airflow

MLflow

Azure DevOps

GitHub Actions

Job description

• Build, improve and maintain machine learning pipelines used within Market Pricing


• Productionise Python-based models, notebooks and data science workflows


• Move models from development into repeatable, tested and documented production processes


• Improve testing, release, monitoring and maintenance of model workflows


• Investigate issues across data, model and pipeline workflows


• Automate manual steps to improve quality, speed or control


• Support Git, code review, testing and documentation practices


• Ensure pipelines and model workflows are traceable, auditable and safe to change


• Collaborate with Pricing, Data Science, Data Engineering, ML Engineering and governance stakeholders


• Own defined MLOps components and pipelines


• Work with senior colleagues on standards, architecture and governance

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 and attention to detail


• Clear communication skills and ability to explain technical ideas to different audiences


• Comfortable working with data scientists, analysts, engineers and business stakeholders


• Practical focus on quality, reliability, governance and maintainability


• Hands-on experience with Azure, AWS or GCP is nice to have


• Exposure to Snowflake, Databricks, Spark or similar is nice to have


• Experience with MLOps practices is nice to have


• Exposure to Airflow, MLflow, Azure DevOps, GitHub Actions or similar is nice to have


• Experience in pricing, insurance, financial services or another regulated environment is nice to have


• Understanding of model governance, responsible AI or explainability is nice to have


• Sponsorship is unavailable for this position


• Successful applicants undergo credit and criminal record checks

Core Competencies

Demonstrates strong capabilities in building and maintaining machine learning pipelines, with a focus on Python programming, SQL proficiency, and MLOps practices. Emphasizes collaboration with cross-functional teams and a commitment to quality, reliability, and governance in data workflows.

Highest-signal resume keywords

• Python Programming


• SQL Proficiency


• MLOps Practices


• Machine Learning Fundamentals


• Git and Code Review

ATS Optimization Keywords

Hard Skills

• Machine Learning Workflows


• Data Pipeline Development


• Automated Testing


• Technical Documentation


• Model Governance

Soft Skills

• Problem-Solving


• Attention to Detail


• Clear Communication

Industry Keywords

• Pricing


• Insurance


• Financial Services


• Regulated Environment


• Responsible AI

Tools & Technologies

• Azure


• AWS


• GCP


• Snowflake


• Databricks


• Spark


• Airflow


• MLflow


• Azure DevOps


• GitHub Actions