Senior 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 Dev Ops 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)

Essential Skills

1. Experience deploying, monitoring and maintaining production services

We’re looking for engineers who have worked hands‑on with:

• Containerisation (Docker) & Service orchestration (Kubernetes or similar)
• Managing and maintaining real‑time endpoints or APIs
• Automated deployment into production environments

This is the most important area of experience for this role.

2. Cloud & Infrastructure Engineering

Experience building or supporting cloud infrastructure for data or predictive services, ideally including:

• Terraform (highly desirable)
• Azure (preferred), or other public cloud platforms
• Infrastructure patterns for scalable, secure services

3. CI/CD Automation

Experience with:

• Azure Dev Ops or Git Hub Actions
• Automated testing, packaging, and deployment processes

CI/CD experience is valuable, but not sufficient on its own without cloud or production‑deployment exposure.

4. Data Ops Experience

We are not looking for profiles focused only on ETL.

However, we will consider candidates who bring Cloud + CI/CD experience alongside technologies such as:

• Proficient SQL; familiarity with PySpark is beneficial
• dbt
• Microsoft Fabric
• SQLMesh

5. Core Engineering Skills

• Strong Python, with good documentation and unit testing practices
• Comfortable in an agile delivery…