LLM Ops Engineer — Databricks Lakehouse & MLOps

Health Business Solutions LLC; Florida; On-site; USD 120,000 - 180,000; Full time

Job summary

Health Business Solutions LLC is seeking an LLM Ops Engineer to own end-to-end ML delivery pipelines on the Lakehouse, with deep Databricks experience. You will ingest data, engineer features, and govern CI/CD, deployment, monitoring, and security.

You will collaborate with Leadership, Data Engineers, and SMEs to productionize models using Delta Lake, Unity Catalog, MLflow, and Feature Store across our cloud environments, delivering reliable GenAI systems.

Qualifications

• BS/MS in Computer Science, Engineering, Data Science, or equivalent practical experience.
• 3+ years of MLOps/ML Engineering/Platform Engineering experience in Databricks.
• Hands-on with Delta Lake, Unity Catalog, MLflow, Feature Store, Workflows/Jobs, Repos, and Model Serving.
• Strong Python engineering skills; familiarity with Spark (PySpark) and SQL.
• Experience with CI/CD (GitHub Actions/Azure DevOps/GitLab) and artifact registries.
• Solid understanding of data/ML pipeline design, data quality checks, and ML evaluation/monitoring.

Responsibilities

• Design and operate Databricks platform including workspaces, clusters, SQL Warehouses, governance, and security.
• Operationalize ML models with MLflow, feature stores, and model registry.
• Build CI/CD for notebooks, repos, and jobs with tests and registry promotions.
• Implement data quality checks, monitoring, and cost optimization.
• Collaborate with data engineers and stakeholders to productionize models.

Skills

Databricks

Python

MLOps

CI/CD

Spark/PySpark

Education

BS/MS in Computer Science, Engineering, Data Science, or equivalent practical experience

Tools

Delta Lake

Unity Catalog

MLflow

Feature Store

Repos

Model Serving

Job description

Health Business Solutions LLC is seeking an LLM Ops Engineer to own end-to-end ML delivery pipelines on the Lakehouse, with deep Databricks experience. You will ingest data, engineer features, and govern CI/CD, deployment, monitoring, and security.

You will collaborate with Leadership, Data Engineers, and SMEs to productionize models using Delta Lake, Unity Catalog, MLflow, and Feature Store across our cloud environments, delivering reliable GenAI systems.