ML Ops Engineer

Role Description

As a Senior MLops Engineers you will play a key role in building and maintaining production‑ready data and machine‑learning systems that support critical business decisions. You’ll work across the full lifecycle, from engaging with stakeholders and shaping data/model outputs, to deploying and maintaining real‑time services in a cloud environment. 

A significant part of this role involves developing and evolving our cloud‑based infrastructure, including containerised applications, automated deployment pipelines, and infrastructure‑as‑code. You’ll also help shape engineering best practices and support the growth of modern, scalable data platforms.

You’ll join our small stream‑aligned agile team, working closely with domain experts to understand business needs and deliver high‑impact solutions.

Location:

This role is hybrid, with the option to work from our London, Bristol, or Bournemouth offices. You’ll be required to attend the office two days per month.

Salary Information

Pay: Circa £60,000 per annum, dependent on experience, skills, and location. 

 
Salary is one part of our wider total reward package.

What You’ll Do

• Design, build, and operate production‑level data and machine‑learning services, including real‑time API endpoints that serve 100k+ requests daily.
• Build and deploy and orchestrate docker containers, optimizing for performance and resource utilization.
• Design, build and maintain cloud R&D solutions using IaC tools like  Terraform.
• Building, improving and maintaining monitoring systems to track model performance, infrastructure health and ensure reliability, scalability, and security of ML systems.
• Develop CICD processes to help automate workflows using tools like Azure DevOps Pipelines/Github Actions and dbt.
• Write high‑quality, well‑tested Python for production‑grade data pipelines and services.
• Deliver data extracts, transformations, and features to support modelling and analytics. We are increasingly using dbt to abstract these processes and would like you to contribute.
• Work within an agile workflow, managing your own tickets and collaborating with team members and across disciplines to deliver products Communicate technical decisions and findings to both technical and non‑technical audiences.
• Taking time to stay up to date with the newest cloud and data tech as you contribute to continuous improvement across cloud tooling, engineering standards, and platform development.

About You (What We’re Looking For)