ML Engineer

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)

Job Type: Contractual / Temporary
Contract length: 3-6 months

Pay: ₹100,000.00 - ₹110,000.00 per month

Benefits:

• Work from home

Application Question(s):

• Do you have Hands-on experience with MLflow, Snowpark, and ML pipeline orchestration is essential?
• Are you comfortable sharing PF details for BGV?
• Do you have experience deploying, monitor, and optimize ML models on Snowflake?

Work Location: Remote