Description

You will build and maintain scalable ML pipelines, deploy models, and manage the end-to-end ML lifecycle.

This role is on-site.

Responsibilities

• Design and build scalable data pipelines and ML infrastructure.
• Deploy and productionize machine learning models.
• Develop scalable tools for ML training and inference.
• Implement CI/CD pipelines and automation for ML workflows.
• Ensure model versioning, auditability, and data security.

Required Skills

• 5+ years of experience in building scalable ML pipelines.
• Strong expertise in Python.
• Proficiency with ML frameworks.
• Experience with cloud platforms.
• Hands-on experience with MLOps tools.
• Ability to implement CI/CD pipelines.
• Support end-to-end model development and PoC deployments.
• Evaluate new technologies to improve system performance and reliability.

Preferred Skills

• Certified Machine Learning Specialty Google Professional Machine Learning Engineer or Azure AI Engineer Associate.
• Databricks or MLflow Certifications.

Key Skills

Education

Any Graduate