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MLOps Engineer

Harnham - Data & Analytics RecruitmentLondon, UK🇬🇧United Kingdom

Why this role stands out

As a remote MLOps Engineer, you'll own critical platform operations and drive MLOps best practices within a large, data-focused organization, offering an excellent daily rate of £550-£650. This role is perfect for a mid-senior professional experienced with Databricks and end-to-end MLOps who thrives in a collaborative, enterprise environment and is eager to step into a position with significant operational impact. Apply today to leverage your expertise and contribute to a company at the forefront of AI and data analytics.

Quick overview

Salary£550 - £650/mo
SeniorityMid Senior
Employment typeFull Time
Work modeHybrid
LocationLondon, UK, United Kingdom

Job description

Senior MLOps Engineer
London (Hybrid) | £75,000 - £95,000 + Bonus + BenefitsThis is an opportunity to take ownership of the infrastructure powering a growing AI platform. You'll work across machine learning, NLP, and emerging AI technologies, helping build scalable systems that support real-world impact.The CompanyA growing AI and data consultancy helping organisations use data and machine learning to improve decision-making and deliver better outcomes. They are investing heavily in their AI platform and expanding their engineering capability.The Role

  • Own and develop the MLOps infrastructure supporting AI services.
  • Build and maintain orchestration pipelines using Dagster, Airflow, or Prefect.
  • Deploy and manage ML workloads on Kubernetes and cloud platforms.
  • Implement CI/CD, observability, and monitoring across production systems.
  • Develop infrastructure using Terraform, Bicep, or similar IaC tools.
  • Work closely with Data Scientists, ML Engineers, and AI teams to scale deployments.

Your Skills & Experience

  • Strong Python software engineering skills.
  • Commercial MLOps experience in production environments.
  • Hands-on Kubernetes expertise.
  • Experience with workflow orchestration platforms.
  • Infrastructure as Code and CI/CD experience.
  • Understanding of production ML, NLP, or AI systems.

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