Senior ML/AI Engineer

or similar model lifecycle management platforms.

Experience working with structured enterprise datasets.

Experience evaluating and implementing both traditional

learning approaches and embedding-based or retrieval-driven architectures (e.g., vector search, similarity matching) is a plus.

Demonstrated ability to select the right technical solution for a given business problem rather than defaulting to a single modeling paradigm.

The duties listed below are the essential functions of this position, and they may change as the needs of the company demand.

Design, build, and deploy machine learning models into production environments, including REST API-based inference services and batch or real-time scoring pipelines.

Develop scalable training and inference pipelines using structured enterprise data.

Establish and maintain

practices including model versioning, monitoring, alerting, retraining workflows, and auditable model lifecycle management.

Collaborate with Data Engineering to ensure AI-ready data structures and pipelines.