AI/ML Engineering Lead
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仕事内容
Lead a team of AI/ML engineers to design, build, test, and maintain production-grade AI systems that solve real-world problems.
Own end-to-end model lifecycle: data ingestion, feature engineering, model training, evaluation, deployment, and ongoing monitoring.
Set and enforce software engineering best practices for ML codebases, including testing, documentation, CI/CD, and versioning.
Architect scalable AI services and pipelines that integrate with existing backend and platform infrastructure, ensuring reliability and observability.
Collaborate with product, data, and platform teams to translate business requirements into robust AI-driven solutions; mentor engineers on Python and system design.
Stay current with ML engineering trends (MLOps, applied ML) and define practical strategies for retraining, monitoring, and debuggability in production.
Own end-to-end model lifecycle: data ingestion, feature engineering, model training, evaluation, deployment, and ongoing monitoring.
Set and enforce software engineering best practices for ML codebases, including testing, documentation, CI/CD, and versioning.
Architect scalable AI services and pipelines that integrate with existing backend and platform infrastructure, ensuring reliability and observability.
Collaborate with product, data, and platform teams to translate business requirements into robust AI-driven solutions; mentor engineers on Python and system design.
Stay current with ML engineering trends (MLOps, applied ML) and define practical strategies for retraining, monitoring, and debuggability in production.
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