Machine Learning Engineer - Snowflake DB

Role : ML Engineer Snowflake

Location : Bengaluru & Chennai

About the Role :

- Build scalable feature engineering, model training, and inference workflows using Snowpark ML

- Manage model lifecycle including versioning, deployment, and governance using Snowflake Model Registry

- Implement and maintain centralized feature management using Snowflake Feature Store

- Leverage Cortex ML functions for forecasting, anomaly detection, and classification use cases

- Develop and optimize Snowpark Python UDFs and vectorized UDFs for real-time and batch model serving

- Orchestrate ML pipelines using Snowflake stored procedures

- Apply MLOps best practices including experiment tracking, model monitoring, and A/B testing

- Collaborate with cross-functional teams and engage with clients to understand business requirements

- Prepare clear technical documentation and present solutions to stakeholders

Technical Skills Required :

- Snowpark ML for feature engineering, model training, and inference

- Snowflake Model Registry for model versioning and deployment

- Snowflake Feature Store for centralized feature management

- Cortex ML functions (forecasting, anomaly detection, classification)

- Snowpark Python UDFs and vectorized UDFs for ML inference

- ML libraries within Snowpark : scikit-learn, XGBoost, LightGBM, PyTorch

- MLOps practices : experiment tracking, monitoring, A/B testing

- Stored procedures for ML pipeline orchestration in Snowflake

Experience & Qualifications :

- Minimum 1 year of hands-on experience deploying ML models on Snowflake

- Proven delivery of 2+ production-grade ML models (forecasting, classification, or recommendation systems)

- Strong understanding of enterprise-scale data and ML architectures

- Excellent communication skills for client interactions and technical documentation

Nice to Have :

- Exposure to data engineering or analytics workflows on Snowflake

- Familiarity with cloud-native ML deployments and governance frameworks