MLOps Engineer

Salary: £? - ? per year

Requirements

• Solid programming skills in Python, plus experience with web libraries such as FastAPI, Flask, or Django
• Hands-on experience with ML model deployment and monitoring in production
• Knowledge of containerization with Docker
• Experience with CI/CD pipelines and cloud environments, particularly Azure

Responsibilities

• Own the infrastructure and delivery pipelines that keep our AI-driven products reliable, scalable, and fast
• Design and maintain our cloud environments, CI/CD workflows, and observability systems so our engineers can ship with confidence
• Implement or improve model monitoring and operational controls for AI/ML systems
• Build and maintain robust ML pipelines for training, deployment, and monitoring
• Develop backend systems and APIs that integrate AI into our SaaS platform
• Take ownership of ML performance, monitoring, availability, and security
• Define drift, unexpected-output, and AI incident playbooks with clear ownership and evidence
• Align our MLOps processes with data governance, AppSec, logging, monitoring, and enterprise GRC expectations
• Support AI-specific control closure across NIST-style controls, SOC 2, ISO 27001, and enterprise GRC contexts
• Create repeatable evidence for monitoring, alerting, response, review, and BAU handover
• Ensure our MLOps controls are sustainable after the remediation programme closes

Technologies

• AI
• Backend
• CI/CD
• Cloud
• Django
• Docker
• FastAPI
• Flask
• Support
• Python
• Security
• Web
• Azure
• Machine Learning

More

We are hiring for our AI Engineering team for a remote MLOps Engineer contract, with occasional travel to our London office. This is an inside IR35 assignment for up to 6 months, starting ASAP, with a day rate of up to £800. The role focuses on building and operating the infrastructure, pipelines, and controls that support our AI-driven products, with an emphasis on reliability, scalability, observability, and governance.

last updated 24 week of 2026