Über
Design and build end-to-end machine learning infrastructure for high-availability production services Automate deployment of low-latency services to enable real-time model inferences across the platform Lead the creation and optimization of a centralized feature store for training complex models
Required qualifications:
3+ years of experience in Platform Engineering with a focus on scalable ML platforms 1+ years of experience managing ML systems end-to-end in production environments Proficiency in streaming architectures (Kafka/Flink/PubSub) and building low-latency services Expertise in MLOps and experience with tools like SageMaker and VertexAI Proficient in Python, with additional skills in Go, C++, or Rust as a strong plus
Sprachkenntnisse
- English
Hinweis für Nutzer
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