Lead ML Ops Engineer

Job Description Roles & Responsibilities 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. This role is ideal for someone who thrives at the intersection of engineering, AI, and operational excellence. Key Responsibilities Own and implement the end-to-end MLOps lifecycle (CI/CD, model registry, monitoring, governance) Design and build CI/CD pipelines for ML systems ensuring secure, scalable deployments Lead model deployment strategies (batch, real-time, streaming) with robust rollback and release controls Establish monitoring & observability frameworks (model performance, drift detection, alerts) Ensure governance, compliance, and audit readiness across ML workflows Drive operational excellence, including incident management, runbooks, and reliability engineering Desired Candidate Profile 8+ years in MLOps / ML Engineering / Data Engineering / DevOps Strong experience with ML lifecycle management (MLflow, model registry, versioning) Proven track record building CI/CD pipelines for ML systems Hands-on experience with Python, cloud platforms, and production ML environments Strong understanding of monitoring, observability, and model performance management Experience working in regulated environments (financial services preferred) Company Industry LegalLaw Firm Department / Functional Area IT Software Keywords Lead ML Ops Engineer Get real-time job updates only on our App