[Remote] Machine Learning Engineer

Lumenalta is seeking an experienced MLOps Engineer to operationalize machine learning at scale on the Databricks platform. The role bridges data engineering and ML, building infrastructure and workflows for reliable production deployments, including MLflow, feature stores, CI/CD, and model monitoring.

• Design and maintain MLflow-based workflows for experiment tracking, model registry, versioning, and lifecycle management
• Build and manage Feature Store infrastructure to enable reusable, consistent feature pipelines across teams and use cases
• Develop model deployment pipelines, including serving infrastructure, A/B testing support, versioning, and rollback strategies
• Implement CI/CD pipelines tailored for ML workflows, including automated testing, validation gates, and deployment triggers
• Orchestrate distributed model training on Databricks, optimizing for compute efficiency, reproducibility, and cost
• Monitor deployed models for data drift, performance degradation, and system health, triggering automated retraining workflows as needed
• Collaborate with Data Scientists and Data Engineers to reduce friction between experimentation environments and production

• 3–5+ years in MLOps, ML platform engineering, or DevOps for ML, with proven production ML deployments