

DevOps Engineer AI/ML
⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for a DevOps Engineer AI/ML on a contract basis, lasting up to "X months," with a pay rate of up to £500 per day. Key skills include ML Ops tools, cloud services (AWS, Azure, GCP), and CI/CD practices.
🌎 - Country
United Kingdom
💱 - Currency
£ GBP
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💰 - Day rate
500
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🗓️ - Date discovered
August 27, 2025
🕒 - Project duration
Unknown
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🏝️ - Location type
Remote
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📄 - Contract type
Outside IR35
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🔒 - Security clearance
Unknown
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📍 - Location detailed
United Kingdom
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🧠 - Skills detailed
#Cloud #Logging #Security #ML (Machine Learning) #Version Control #Compliance #SageMaker #AI (Artificial Intelligence) #DevOps #AWS (Amazon Web Services) #Docker #MLflow #Monitoring #Deployment #Kubernetes #Azure #Data Science #Scala #ML Ops (Machine Learning Operations) #GCP (Google Cloud Platform)
Role description
OUTSIDE IR35 + REMOTE – UP TOO £500 P/D
Inspirec has partnered with a dynamic and innovative leader in the technology industry, who are seeking a highlymotivated AI/ML DevOps Engineer to join their team on a contract basis.
We are seeking an experienced ML Ops / DevOps Engineer to manage the deployment, monitoring, and lifecycle of AI/ML solutions. This role ensures the reliability, security, and auditability of machine learning models in production environments, supporting scalable and compliant AI operations.
Key Responsibilities:
• Design, build, and maintain robust deployment pipelines for machine learning models.
• Monitor model performance and data drift; manage retraining and redeployment processes.
• Ensure version control, reproducibility, and auditability of all AI/ML assets.
• Implement effective logging, monitoring, and alerting for AI services and infrastructure.
• Guarantee adherence to security, governance, and infrastructure standards, especially in regulated environments.
• Collaborate closely with data scientists and software engineers to productionize prototypes into scalable, maintainable solutions.
Essential Skills & Experienc:
• Hands-on experience with ML Ops tools such as MLflow, Kubeflow, Amazon SageMaker, Vertex AI, orequivalent platforms.
• Deep understanding of cloud infrastructure services (AWS, Azure, GCP).
• Strong experience with CI/CD practices and containerization tools (Docker, Kubernetes).
• Knowledge of the machine learning model lifecycle, including drift detection and automated retraining.
• Familiarity with information security best practices and compliance standards, particularly in government or highly regulated contexts.
OUTSIDE IR35 + REMOTE – UP TOO £500 P/D
Inspirec has partnered with a dynamic and innovative leader in the technology industry, who are seeking a highlymotivated AI/ML DevOps Engineer to join their team on a contract basis.
We are seeking an experienced ML Ops / DevOps Engineer to manage the deployment, monitoring, and lifecycle of AI/ML solutions. This role ensures the reliability, security, and auditability of machine learning models in production environments, supporting scalable and compliant AI operations.
Key Responsibilities:
• Design, build, and maintain robust deployment pipelines for machine learning models.
• Monitor model performance and data drift; manage retraining and redeployment processes.
• Ensure version control, reproducibility, and auditability of all AI/ML assets.
• Implement effective logging, monitoring, and alerting for AI services and infrastructure.
• Guarantee adherence to security, governance, and infrastructure standards, especially in regulated environments.
• Collaborate closely with data scientists and software engineers to productionize prototypes into scalable, maintainable solutions.
Essential Skills & Experienc:
• Hands-on experience with ML Ops tools such as MLflow, Kubeflow, Amazon SageMaker, Vertex AI, orequivalent platforms.
• Deep understanding of cloud infrastructure services (AWS, Azure, GCP).
• Strong experience with CI/CD practices and containerization tools (Docker, Kubernetes).
• Knowledge of the machine learning model lifecycle, including drift detection and automated retraining.
• Familiarity with information security best practices and compliance standards, particularly in government or highly regulated contexts.