Manager, ML Engineering
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仕事内容
Lead the architectural design of scalable ML systems, integrating data pipelines (Airflow, dbt) with cloud infrastructure (GCP) for enterprise use.
Own the full ML lifecycle for high-priority initiatives, including resource planning, sprint management, and production rollout.
Partner with Marketing, Supply Chain, and Finance to translate business problems into technical requirements and data-driven narratives.
Ensure production excellence through MLOps, security, reliability, and governance that meet enterprise standards.
Conduct design reviews and code audits to enforce Software Engineering for ML best practices across the team.
Incorporate Generative AI and LLM-driven approaches to augment traditional ML workflows and automation.
Own the full ML lifecycle for high-priority initiatives, including resource planning, sprint management, and production rollout.
Partner with Marketing, Supply Chain, and Finance to translate business problems into technical requirements and data-driven narratives.
Ensure production excellence through MLOps, security, reliability, and governance that meet enterprise standards.
Conduct design reviews and code audits to enforce Software Engineering for ML best practices across the team.
Incorporate Generative AI and LLM-driven approaches to augment traditional ML workflows and automation.
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