Senior MLOps Engineer

🚀 Senior MLOps Engineer (Databricks / MLflow)

£500/day (Inside IR35) | 3-Month Rolling Contract | Likely Extension

Remote (UK-based) | Start: 13th or 20th April

We’re working with a fast-growing, practitioner-led data & AI consultancy delivering production-grade machine learning systems for major UK and global brands across financial services, retail, and beyond.

They’re looking for a Senior MLOps Engineer to take ownership of building and scaling real-world ML environments — not just proof of concepts.

This is a hands-on role where you’ll play a key part in getting models into production and making them reliable, scalable, and maintainable.

🧠 The Role

You’ll be responsible for end-to-end ML lifecycle delivery, working closely with data science and engineering teams across client engagements.

Key responsibilities include:

• Building and owning ML pipelines (training → deployment → monitoring)
• Productionising models built in PyTorch, TensorFlow, or Scikit-learn
• Using MLflow for experiment tracking, model versioning, and deployment
• Developing scalable pipelines in Databricks (Delta, DLT, Jobs)
• Designing and maintaining Azure-based data platforms (Data Lake, Synapse)
• Implementing CI/CD pipelines for ML and data workflows
• Automating infrastructure using Terraform / ARM / Ansible

🧰 Tech Stack

• Databricks + MLflow (core focus)
• Azure (Data Lake, Synapse, SQL DW)
• Python, SQL, PySpark
• CI/CD: Azure DevOps, Git, Jenkins
• Infrastructure as Code: Terraform, ARM, Ansible

✅ What We’re Looking For

• Strong experience in MLOps / ML Engineering / Data Engineering
• Proven track record of deploying ML models into production
• Hands-on expertise with Databricks and MLflow

If you’re an MLOps engineer who enjoys building, not just designing, and you’re available to start in April, I’d be keen to speak.