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.