Principal ML System Engineer

📋 Description

• Partner with product and engineering leadership to translate objectives into a multi-quarter
• Define architectures and standards for scalable data and ML pipelines for training, evaluation
• Set direction for MLOps, including CI/CD for models, model registry, feature stores, and experiment
• Establish reliability, observability, and performance practices for ML systems in production
• Define secure integration patterns with existing systems, ensuring authentication, RBAC, audit
• Provide technical leadership and mentorship across engineering teams for ML infrastructure.

🎯 Requirements

• Expert level in Python and Java with strong software engineering fundamentals.
• Extensive experience designing/building ML platforms and ML Ops at scale; familiarity with MLFlow
• Extensive cloud experience (AWS, Azure, and/or GCP), containerization (Docker), and orchestration
• Proven track record setting technical direction and driving cross-team initiatives.