🚀 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.