ML Engineer (Snowflake & MLflow) PF Mandatory
Posted on September 9, 2025
Job Description
- Requirement: ML Engineer (Snowflake & MLflow) PF Mandatory
- Mode: C2C / Remote
- Experience: 5-8 years
- Budget: 1.1 lpm + gst
- Job Description:
- Must Have Skills: ML Engineer, Snowflake & MLflow
- External Description:
- We are seeking an ML Engineer with strong expertise in deploying, monitoring, and managing machine learning pipelines on Snowflake. The ideal candidate will act as a bridge between the Data Engineering team and the ML team, ensuring seamless integration of ML models into production workflows.
- Hands-on experience with MLflow, Snowpark, and ML pipeline orchestration is essential.
- Deploy, monitor, and optimize ML models on Snowflake.
- Design and maintain end-to-end ML pipelines (training, validation, deployment, monitoring).
- Use MLflow for experiment tracking, model registry, and performance monitoring.
- Collaborate with Data Engineers on data ingestion, transformations, and model-ready datasets.
- Implement MLOps best practices (CI/CD for ML, model versioning, reproducibility).
- Support performance tuning of ML models and pipelines.
- Provide governance and documentation for ML workflows.
- ML Engineering: ML pipeline design, model deployment, monitoring, and retraining.
- Snowflake: Strong knowledge of Snowflake platform, Snowpark, and SQL.
- MLflow: Hands-on experience with experiment tracking, model registry, and monitoring.
- Programming: Python (pandas, numpy, scikit-learn, PySpark).
- DevOps/MLOps: CI/CD pipelines, version control (GitHub), containerization (Docker), orchestration (Airflow/Databricks workflows).
Required Skills
No specific skills listed.