ML Ops Engineer (Databricks Experience) - 12 Months FTC

Lorien; West Midlands; Hybrid; GBP 35,000 - 59,000; Full time

Benefits offered by this job

Hybrid working

Pension with matched contributions

Life assurance 6x salary

28 days leave + bank holidays

Ongoing training and development

Job summary

Lorien is hiring an ML Ops Engineer in the UK to design, build, and optimise scalable machine learning pipelines and data platforms. You will enable industrialised ML models and data solutions, contributing to governance, monitoring, and governance best practices.

You will collaborate with data scientists, engineers and stakeholders to deliver high-quality solutions and continuously improve tooling and engineering standards.

Qualifications

• Experience in ML Ops and data engineering within an Agile environment.
• Proficient with Databricks and cloud data tooling (AWS: S3, Glue, Redshift, SageMaker).
• Strong programming skills in Python and SQL (and/or Spark).
• Hands-on ML model deployment, monitoring and lifecycle management.

Responsibilities

• Design, build and maintain scalable ML pipelines and data workflows.
• Support deployment, monitoring and lifecycle management of ML models in production.
• Automate processes to improve efficiency, reliability and performance.

Skills

ML Ops experience

Data engineering

Python

SQL

Spark

Databricks

Docker

Kubernetes

AWS data tooling

Model deployment

Data pipelines

Agile

Tools

Databricks

Docker

Kubernetes

S3/Glue/Redshift/SageMaker

Job description

You will join one of the UK's leading financial services companies, where innovation and continuous improvement are at the heart of everything they do. The business is undergoing an exciting transformation in how data and machine learning capabilities are developed, deployed and scaled to better serve customers and stakeholders.

Our client is looking for an ML Ops Engineer to play a key role in designing, building and optimising machine learning pipelines and data platforms. This is a highly impactful role, enabling the organisation to industrialise machine learning models and deliver scalable, reliable and efficient data solutions.

Key Responsibilities

• Design, build and maintain scalable machine learning pipelines and data workflows
• Support the deployment, monitoring and life cycle management of ML models in production
• Improve and automate processes to enhance efficiency, reliability and performance
• Develop robust data engineering solutions to support analytics and ML use cases
• Ensure best practices in model governance, monitoring, and observability are followed
• Collaborate with data scientists, engineers and stakeholders to deliver high-quality solutions
• Contribute to continuous improvement of tools, frameworks and engineering standards

Essential Skills

• Proven experience in ML Ops, data engineering or a related field within a commercial/Agile environment
• Databricks
• Strong programming skills in Python, SQL and/or Spark
• AWS data tooling such as S3/Glue/Redshift/SageMaker (Or relevant experience in another cloud technology)
• Hands-on experience with ML model deployment, monitoring and life cycle management
• Experience building and maintaining data pipelines and workflow orchestration
• Understanding of containerisation and infrastructure tools (eg Docker, Kubernetes)

Benefits

• Salary up to £59,000 + up to 20% bonus
• Hybrid working: Once a week or fortnight in the office
• 28 days holiday plus bank holidays (option to buy and sell)
• Life assurance (6x annual salary)
• Personal pension with matched contributions
• Ongoing training and opportunities for development