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MLOps Engineer

Thelanesgroup — United Kingdom · Posted ~4 hours ago

Hybrid £85000-£95000 + benefits

Skills

MLOps machine learning deployment model serving CI/CD model monitoring observability containerization cloud infrastructure model versioning reproducibility Docker Cloud Model Monitoring Model Serving

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Summary ✨ AI‑Generated

A hybrid MLOps opportunity within a fast-growing technology environment, bridging machine learning, data, and platform engineering. You will build deployment and model-serving infrastructure, automate CI/CD for ML workloads, implement monitoring and observability, manage containers and cloud infrastructure, and help move models reliably from experimentation into secure production.

Highlights

Well-compensated hybrid MLOps role focused on production machine learning, scalable infrastructure, automation, monitoring, observability, reproducibility, and close collaboration with data and ML engineering teams.

Description

MLOps Engineer – Manchester Location: Manchester (Hybrid) Salary: £85,000 - £95,000 + Benefits About Our Client Our client is a fast-growing technology business building machine learning products used across a large customer base. As its AI capability scales, they are expanding the engineering team responsible for deploying, monitoring and operating production machine learning systems. The Role You will bridge Machine Learning, Data and Platform Engineering, creating reliable infrastructure and processes that allow models to move efficiently from experimentation into secure, scalable production environments. Key Responsibilities Build and maintain ML deployment and model-serving infrastructure.Develop automated CI/CD pipelines for machine learning workloads.Implement model monitoring, observability and performance tracking.Work with Data Scientists and ML Engineers to productionise models.Manage containerised workloads and cloud infrastructure.Improve model versioning, reproducibility and experiment tracking.Automate infrastructure using Infrastructure as Code.Support security, scalability and reliability of production AI services. Skills & Experience Commercial MLOps, ML Engineering, DevOps or Platform Engineering experience.Strong Python skills and experience with machine learning workflows.Experience with Docker, Kubernetes and CI/CD tooling.Knowledge of AWS, Azure or GCP.Experience with MLflow, Kubeflow, SageMaker, Azure ML or comparable tooling.Terraform or other Infrastructure as Code experience.Understanding of monitoring, observability and production ML lifecycle management. Package £85,000 - £95,000 + BenefitsManchester – hybrid workingPerformance-related bonus and/or equity depending on rolePrivate healthcareEnhanced pension contribution25 days annual leave plus bank holidaysFlexible working arrangementsProfessional development budgetClear progression within a growing technology function Apply If you are interested in this opportunity, please apply with your latest CV. Suitable applicants will be contacted to discuss the position, client and package in more detail.