Lead MLOps Engineer

Requisitos

• 5+ years of experience in MLOps or ML platform engineering, with a proven track record of leading technical initiatives end-to-end
• Deep expertise in ML model lifecycle management, including versioning, configuration management, and rollback, with experience defining o..
• Strong background in architecting signal computation pipelines, covering scheduled refresh, provenance capture, and grain translation
• Advanced proficiency in calibration methodology: holdout discipline, configuration sweep design, and catch-rate vs. scope measurement
• Expert knowledge of as-of temporal data systems or back-test harness design and operation

Desejáveis

• Familiarity with Snowflake ML or Snowpark in production settings
• Proven showcase of embedding model versioning and controlled reindex orchestration at scale
• Operational leadership with pgvector or vector store management
• Background in gaming domain or QA tooling