ML Engineer (Databricks focused)
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Job Description
Structured overview of role & requirementsAbout This Role
Own end-to-end development and deployment of machine learning models using Databricks platform including MLflow, Delta Lake, Unity Catalog, and Databricks Workflows.
Implement feature engineering, hyperparameter tuning, model evaluation, and monitoring for ML systems in production.
Work remotely focusing on measurable outcomes through senior-level technical contributions in Machine Learning engineering with AWS and cloud platform integration.
Minimum Requirements
5+ years of experience in Machine Learning, Data Science, or AI-related roles.
Mandatory strong hands-on experience with Databricks and associated components (MLflow, Delta Lake, Unity Catalog, Databricks Workflows).
Proficiency in Python, PySpark, SQL, Spark; experience with ML frameworks like Scikit-learn, TensorFlow, PyTorch, XGBoost, or LightGBM.
Bachelor's or Master's degree in Computer Science, Data Science, Statistics, AI, or related fields.
Ideal Candidate Profile
Experienced ML Engineer with deep expertise operating within the Databricks ecosystem and cloud platforms (AWS, Azure, or GCP).
Capable of developing production-grade ML pipelines integrating CI/CD and MLOps best practices.
Senior-level practitioner able to collaborate with architects and practice leadership, delivering measurable technical impact remotely.