556534_DNACRL_ML Engineer_India

Description:
Core Requirements
• Design and implementation of end-to-end ML solutions from data ingestion to production
• Strong experience with Amazon Databricks and PySpark
• Building scalable batch (and near-real-time) data & ML pipelines
• Experience with Delta Lake and analytics-ready data models
Data Analysis & Modeling
• Performing exploratory data analysis (EDA) on large datasets
• Feature engineering and data validation at scale
• Designing, training, and iterating on ML models
• Model testing, evaluation, and selection using appropriate metrics
• Experience with multi-stage / chained ML models
MLOps & ML Lifecycle
• Deep hands-on experience with MLflow
• Experiment tracking
• Model comparison and selection
• Model versioning & registry
• Managing continuous experimentation and improvement
• Refactoring research code into production-grade ML pipelines
Deployment & Monitoring
• Model deployment via Databricks Model Serving and/or batch inference
• CI/CD for ML pipelines
• Implementing model monitoring, including data and prediction drift
• Defining retraining and rollback strategies
Collaboration
• Ability to work independently and with cross-functional teams
• Clear documentation and production ownership mindset

Additionally (nice to have):
• Solid experience with AWS (S3, IAM, CloudWatch)
• Git-based development and testing best practices

Amazon Databricks and PySpark, Delta Lake and analytics-ready data models, Deep hands-on experience with MLflow