Engineering Manager, Machine Learning Infrastructure, Ads
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The role
Lead a team of ML infrastructure engineers to build scalable production-ready ML systems for ads, including training, data pipelines, feature engineering, and inference.
Own the architecture and drive best practices for scalability, reliability, and cost-effectiveness across training, serving, and feature stores.
Collaborate with data scientists, ML engineers, platform teams, and product stakeholders to design, implement, and operate robust ML platforms.
Own end-to-end delivery from data ingestion to serving in production.
Recruit, mentor, and grow a high-performing team.
Define the roadmap and execute initiatives to accelerate model development and deployment at scale.
Own the architecture and drive best practices for scalability, reliability, and cost-effectiveness across training, serving, and feature stores.
Collaborate with data scientists, ML engineers, platform teams, and product stakeholders to design, implement, and operate robust ML platforms.
Own end-to-end delivery from data ingestion to serving in production.
Recruit, mentor, and grow a high-performing team.
Define the roadmap and execute initiatives to accelerate model development and deployment at scale.
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