The AI/ML Engineer is responsible for designing, deploying, and scaling production machine learning models for business-critical use cases. This role owns the end-to-end ML lifecycle —from feature engineering and model training to deployment and monitoring—while applying MLOps and responsible AI practices . The engineer collaborates with cross-functional teams to deliver scalable, reliable, and production-ready AI solutions.

Responsibilities

• Own end-to-end ML model development from design and training to deployment and monitoring
• Design and manage feature pipelines using Snowpark Feature Store with proper versioning and governance
• Build and optimize training workflows and production inference services (APIs, REST/gRPC, FastAPI)
• Design scalable inference systems with latency, throughput, and cost optimization
• Productionize ML models in Snowflake and AWS ...