Lead ML Ops Engineer

<div><p>We are partnering with a<b>leading financial services organisation</b>to hire a<b>Lead MLOps Engineer</b>to play a critical role in scaling enterprise AI capabilities.</p><p>This is an opportunity to take ownership of the<b>end-to-end MLOps lifecycle</b>, ensuring AI models are reliably deployed, monitored, and maintained in a<b>highly regulated, production environment</b>.</p><h3>The Opportunity</h3><p>You will sit within a high-performing AI squad, working closely with Data Scientists, AI Engineers, and platform teams to bring machine learning models into production at scale.</p><p>This role is ideal for someone who thrives at the intersection of<b>engineering, AI, and operational excellence</b>.</p><h3>Key Responsibilities</h3><ul><li>Own and implement the<b>end-to-end MLOps lifecycle</b>(CI/CD, model registry, monitoring, governance)</li><li>Design and build<b>CI/CD pipelines for ML systems</b>ensuring secure, scalable deployments</li><li>Lead<b>model deployment strategies</b>(batch, real-time, streaming) with robust rollback and release controls</li><li>Ensure<b>governance, compliance, and audit readiness</b>across ML workflows</li><li>Drive<b>operational excellence</b>, including incident management, runbooks, and reliability engineering</li></ul><h3>What We’re Looking For</h3><ul><li>8+ years in<b>MLOps / ML Engineering / Data Engineering / DevOps</b></li><li>Strong experience with<b>ML lifecycle management (MLflow, model registry, versioning)</b></li><li>Proven track record building<b>CI/CD pipelines for ML systems</b></li><li>Hands-on experience with<b>Python, cloud platforms, and production ML environments</b></li><li>Strong understanding of<b>monitoring, observability, and model performance management</b></li><li>Experience working in<b>regulated environments (financial services preferred)</b></li></ul></div>#J-18808-Ljbffr