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snowflake python kubernetes airflow kafka📋 Description
- Lead and grow a high-performing data/ML engineering team.
- Architect scalable ML data pipelines for batch and real-time inference.
- Build foundational Content Trust data layers: embeddings, metadata, signals.
- Partner on AI/LLM integration with Search & Discovery teams.
- Drive operational excellence with SLAs for fast, explainable infra.
- Collaborate cross-functionally to meet regulatory needs with robust architectures.
🎯 Requirements
- 8+ years engineering, 3+ in people mgmt within Data/ML Eng.
- Scale: prod-grade pipelines for 100M+ entities (Spark/Flink/Kafka/Airflow)
- ML Infra: ML lifecycle, features, deployment (MLOps), vector DBs
- Trust & Safety: experience with content moderation, fraud/spam, or DRM
- Tech breadth: Python/Scala/Go; AWS/GCP, Kubernetes, Snowflake
- Strategic comms: explain trade-offs to non-tech stakeholders (Legal/Policy/Product)
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