ML ops Engineer

Location : Remote

Job Type : Full-Time / freelance

‍ Experience : 3–8 Years (Databricks + MLOps)

Job Summary

We are looking for an experienced Databricks MLOps Engineer with strong hands-on expertise in Databricks, MLflow, Delta Lake, and end-to-end ML pipeline management. The role involves deploying, monitoring, and optimizing production ML models across cloud environments while collaborating with Data & AI teams.

Key Responsibilities

Manage Databricks Workspaces, Jobs, Workflows, Unity Catalog & MLflow

Handle full ML lifecycle : training, deployment, monitoring, retraining

Build scalable ML / data pipelines (Python, PySpark, SQL)

Deploy ML infrastructure on AWS / Azure / GCP

Use Terraform, Docker, Kubernetes for infra automation

Build CI / CD pipelines (GitHub Actions / Jenkins / GitLab)

Configure model monitoring & drift detection

Work with Feature Store, Optuna, Ray Tune

Document processes & collaborate across teams

Required Skills

Databricks, MLflow, Delta Lake, Unity Catalog

Python, PySpark, SQL

Terraform, Docker / Kubernetes

Cloud : AWS / Azure / GCP

CI / CD for ML workflows

Model monitoring (SHAP, LIME)

How to apply

interested candidates can apply directly throught linkedin or share thier profiles with contact details.

DM-6300575610