advanced professional handling complex enterprise AI/ML deployments

• Design robust, scalable AI/ML solutions utilizing the full Snowflake native stack and partner ecosystem.
• Perform deep-dive Root Cause Analysis (RCA) for complex system dependencies in AI/ML solutions.
• Collaborate cross-functionally with Sales and Product teams to align technical roadmaps with customer ROI.
• Mentor Level 3 architects on best practices for MLOps and architectural design.

TECHNICAL DEPTH & RISK MANAGEMENT:

• Distributed Systems: Deconstruct failures in complex pipelines involving external cloud services (AWS/Azure/Google Cloud Platform).
• Predictive Failure Analysis: Critically think about potential failure modes like model drift and data skew early in the lifecycle.
• Governance: Architect data security and access controls specifically for sensitive AI/ML training data.

SNOWFLAKE-NATIVE TECH STACK:

• Snowflake Model Registry, Cortex Functions, Python, External MLOps (Kubeflow/SageMaker).

• Reduction in post-deployment technical debt; Regional success of complex implementations; Peer mentorship impact.
• Thorough understanding of the complete Data Science life-cycle including feature engineering, model development, model deployment and model management.

• Experience with GenerativeAI, LLMs and Vector Databases.
• Experience with Databricks/Apache Spark.
• Experience implementing data pipelines using ETL tools.
• Experience working in a Data Science role.
• Proven success at enterprise software.
• Vertical expertise in a core vertical such as FSI, Retail, Manufacturing, etc.

Snowflake is growing fast, and we’re scaling our team to help enable and accelerate our growth. We are looking for people who share our values, challenge ordinary thinking, and push the pace of innovation while building a future for themselves and Snowflake.