ML Ops Lead
Core
Lead the assessment, design, and hands-on implementation of scalable data and ML infrastructure to support AI-powered workforce development platforms.
Role type
Staff / Principal MLOps Engineer
Builds
Production data pipelines, ML workflows, and robust data architecture for workforce development AI
Domain
AI / Machine Learning / Data Engineering / Workforce Technology
Deliverable
production ML models | infrastructure
Required skills
MLOps leadership, complex system diagnosis, systems design, hands-on coding, production pipeline operations, cloud infrastructure fluency
Preferred skills
MLOps practice establishment (CI/CD, experiment tracking, feature stores), mission-driven data experience, public thought leadership, team mentoring
Technologies
SQL, Python, Airflow, dbt, PostgreSQL, Redshift, MongoDB, AWS SageMaker, AWS (S3, Lambda, Glue)
Responsibilities
Evaluate current pipelines and data architecture to produce a prioritized improvement plan; Design durable data and ML systems anchored in customer needs; Rebuild and harden pipelines and upgrade architecture hands-on; Establish patterns for observability, reliability, and data quality
Seniority
Staff / Principal, hands-on IC with strategic ownership
