Senior ML Ops Leader - Enterprise AI Platform (Hybrid)

Principal Financial Group; Charlotte (NC); Hybride; USD 127 000 - 191 000; Plein temps

Avantages offerts par ce poste

Flexible Time Off

Pension Plan

Hybrid Work Environment

Résumé du poste

Principal Financial Group is seeking a Sr Engineer II (Team Leader, Model Operations & Enablement) to lead the MOE team that builds and runs Principal's Enterprise AI pipeline platforms. You’ll coordinate with data science, engineering, and business stakeholders to standardize model movement from idea to production and keep models healthy in production.

You will drive end-to-end responsibilities including model training, deployment, monitoring, drift detection, and expanding LLMOps coverage

Qualifications

• Degree or higher in a technical field; 8+ years of relevant work experience.
• Formal leadership experience in managing a technical team and mentoring staff.
• Experience in MLOps, ML infrastructure, or model-operations work.
• Familiarity with agile methodologies and production monitoring.

Responsabilités

• Lead the MOE team across model training, deployment, monitoring, and maintenance.
• Own and simplify the enterprise AI pipeline architecture and tooling.
• Set 6–12 month strategic direction for MOE platform expansion and drift detection.
• Coordinate with data science and analytics partners to scope and operationalize ML products.
• Guide cross-team collaboration and migrate legacy models to the enterprise MLOps pipeline.
• Ensure change-management rigor in a regulated insurance/financial services environment.

Connaissances

Leadership

MLOps

CI/CD

Agile

Communication

Problem-solving

Formation

Bachelor's degree in CS/related field

Outils

SageMaker

Snowflake

PyTorch

XGBoost

Scikit-Learn

Description du poste

Principal Financial Group is seeking a Sr Engineer II (Team Leader, Model Operations & Enablement) to lead the MOE team that builds and runs Principal's Enterprise AI pipeline platforms. You’ll coordinate with data science, engineering, and business stakeholders to standardize model movement from idea to production and keep models healthy in production.

You will drive end-to-end responsibilities including model training, deployment, monitoring, drift detection, and expanding LLMOps coverage