Responsibilities

- Design, implement, and manage end-to-end ML pipelines for model training, testing, and deployment

- Deploy and maintain machine learning models in production environments

- Develop and optimize data pipelines using SQL (mandatory)

- Work closely with Data Scientists and Data Engineers to operationalize ML models

- Build and maintain CI/CD pipelines for ML workflows

- Monitor model performance and ensure scalability and reliability

- Utilize Databricks for data engineering, model development, and deployment

- Ensure best practices in data governance, versioning, and reproducibility

- Troubleshoot and resolve production issues efficiently

Qualifications

- Robust experience in ML Ops (Model Deployment, Monitoring, CI/CD)

- Hands-on experience with Databricks

- Strong SQL expertise (mandatory) for data manipulation and pipeline development

- Good communication and stakeholder management skills

- Experience with cloud platforms (AWS/Azure/GCP)

- Bachelor’s or Master’s degree in Computer Science, Engineering, or related field

- 4+ years of relevant experience in ML Ops / Data Engineering / ML Engineering

Skills: databricks,ml,ops

📌 MLOP's Engineer (India)
🏢 Commergence
📍 India