We are seeking a Senior MLOps Engineer to help design and build an enterprise-scale machine learning platform from the ground up. This is a unique opportunity to establish a modern MLOps ecosystem on Snowflake, supporting end-to-end model development, deployment, and lifecycle management. The platform will be built on a medallion architecture (Bronze, Silver, Gold), enabling machine learning models to consume trusted, governed data products with full lineage, scalability, and performance. This role will play a key part in shaping standards, processes, and tooling as the platform evolves from MVP to enterprise scale.

Key Responsibilities:

• Architect and build a production-grade MLOps platform on Snowflake, leveraging Snowpark, Snowflake ML, Model Registry, and Feature Store
• Design and operationalize reusable pipelines for training, validation, deployment, inference, and monitoring
• Align ML workflows with Bronze, Silver, and Gold medallion layers to ensure consistent use of trusted data
• Establish model lifecycle management standards, including versioning, approvals, promotion gates, and rollback strategies
• Partner with data scientists to productionize models into scalable, reliable services
• Implement model observability for performance, drift, bias, and data quality, with alerting and SLOs
• Automate retraining and refresh processes using Snowflake Tasks, Dynamic Tables, and event-driven orchestration
• Collaborate with data engineering teams to ensure reliable and reusable feature pipelines
• Define and implement CI/CD pipelines for ML systems, including testing frameworks and release controls
• Drive governance across security, compliance, auditability, reproducibility, and responsible AI practices
• Lead platform maturation, including documentation, developer enablement, and operational runbooks