• Build and manage ML pipelines in Databricks for model deployment and monitoring.
• Implement automated retraining workflows based on performance metrics.
• Integrate pipelines with agentic AI applications for seamless updates.
• Ensure compliance with data governance and security standards.
• Collaborate with data scientists and AI engineers to operationalize models.

Requirements

Strong experience with Databricks, MLflow, and CI/CD for ML
Knowledge of agentic AI workflows and orchestration
Proficiency in Python, SQL, and distributed data processing
Familiarity with cloud platforms (AWS or Azure) and containerization
Understanding of GitHub Actions and DevOps principles for ML pipelines
Experience with Hugging Face, BERT, and transformer-based models
Preferred Certifications: Databricks Certified Data Engineer or ML Professional.

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Hard Skills

ML pipelines
automated retraining workflows
Python
SQL
distributed data processing
Databricks
MLflow
Hugging Face
BERT
transformer-based models

Soft Skills

collaboration

Certifications & Qualifications

Databricks Certified Data Engineer
ML Professional

MLOps Engineer

GenAI Engineer, Agentic Flows – Evaluation

Director, MLOps

Machine Learning Engineer

Senior Software Developer – AI Platform