MLOps Engineer
Posted on Jun 5, 2026 by CV-Library
London, United Kingdom
IT
Immediate Start
£700 - £800 Daily
Contract/Project
MLOps Engineer
Location: Remote (Occasional travel to their London office)
Contract: Inside IR35
Day rate: Up to £800 per day
Duration: 6 months
Start date: ASAP
Key words: Machine Learning, Python, containerization (Docker), CI/CD, Azure
As part of our Client's AI Engineering team, you will own the infrastructure and delivery pipelines that keep our AI-driven products reliable, scalable, and fast. You will design and maintain the cloud environments, CI/CD workflows, and observability systems that enable our engineers to ship with confidence.
Key Skills:
- Solid programming skills in Python (plus experience with web libraries like FastAPI, Flask, or Django)
- Hands-on experience with ML model deployment and monitoring in production Knowledge of containerization (Docker)
- Experience with CI/CD pipelines and cloud environments (we use Azure)
Assignment Objectives
- 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 the ML performance, monitoring, availability, and security
- Define drift, unexpected-output and AI incident playbooks with clear ownership and evidence.
- Align 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 MLOps controls are sustainable after the remediation programme closes
Location: Remote (Occasional travel to their London office)
Contract: Inside IR35
Day rate: Up to £800 per day
Duration: 6 months
Start date: ASAP
Key words: Machine Learning, Python, containerization (Docker), CI/CD, Azure
As part of our Client's AI Engineering team, you will own the infrastructure and delivery pipelines that keep our AI-driven products reliable, scalable, and fast. You will design and maintain the cloud environments, CI/CD workflows, and observability systems that enable our engineers to ship with confidence.
Key Skills:
- Solid programming skills in Python (plus experience with web libraries like FastAPI, Flask, or Django)
- Hands-on experience with ML model deployment and monitoring in production Knowledge of containerization (Docker)
- Experience with CI/CD pipelines and cloud environments (we use Azure)
Assignment Objectives
- 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 the ML performance, monitoring, availability, and security
- Define drift, unexpected-output and AI incident playbooks with clear ownership and evidence.
- Align 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 MLOps controls are sustainable after the remediation programme closes
Reference: 225209590
https://jobs.careeraddict.com/post/113361943
MLOps Engineer
Posted on Jun 5, 2026 by CV-Library
London, United Kingdom
IT
Immediate Start
£700 - £800 Daily
Contract/Project
MLOps Engineer
Location: Remote (Occasional travel to their London office)
Contract: Inside IR35
Day rate: Up to £800 per day
Duration: 6 months
Start date: ASAP
Key words: Machine Learning, Python, containerization (Docker), CI/CD, Azure
As part of our Client's AI Engineering team, you will own the infrastructure and delivery pipelines that keep our AI-driven products reliable, scalable, and fast. You will design and maintain the cloud environments, CI/CD workflows, and observability systems that enable our engineers to ship with confidence.
Key Skills:
- Solid programming skills in Python (plus experience with web libraries like FastAPI, Flask, or Django)
- Hands-on experience with ML model deployment and monitoring in production Knowledge of containerization (Docker)
- Experience with CI/CD pipelines and cloud environments (we use Azure)
Assignment Objectives
- 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 the ML performance, monitoring, availability, and security
- Define drift, unexpected-output and AI incident playbooks with clear ownership and evidence.
- Align 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 MLOps controls are sustainable after the remediation programme closes
Location: Remote (Occasional travel to their London office)
Contract: Inside IR35
Day rate: Up to £800 per day
Duration: 6 months
Start date: ASAP
Key words: Machine Learning, Python, containerization (Docker), CI/CD, Azure
As part of our Client's AI Engineering team, you will own the infrastructure and delivery pipelines that keep our AI-driven products reliable, scalable, and fast. You will design and maintain the cloud environments, CI/CD workflows, and observability systems that enable our engineers to ship with confidence.
Key Skills:
- Solid programming skills in Python (plus experience with web libraries like FastAPI, Flask, or Django)
- Hands-on experience with ML model deployment and monitoring in production Knowledge of containerization (Docker)
- Experience with CI/CD pipelines and cloud environments (we use Azure)
Assignment Objectives
- 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 the ML performance, monitoring, availability, and security
- Define drift, unexpected-output and AI incident playbooks with clear ownership and evidence.
- Align 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 MLOps controls are sustainable after the remediation programme closes
Reference: 225209590
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