AI/ML – Data Infrastructure Stream Processing Engineer, Siri Search & Knowledge Platform


Job Overview

Key Qualifications

  • Passionate about Data Processing and Streaming Technologies
  • Experience configuring and troubleshooting realtime processing systems (Flink, Spark Streaming, Samza, Kafka Streams or Storm)
  • Experience building, tuning and troubleshooting stateful stream processing applications
  • Experience with alerting, monitoring and remediation automation in a large scale distributed environment
  • Extensive programming experience in Scala, Java, Python or Go
  • Interest or knowledge in using public or private Kubernetes frameworks for scaling data and services infrastructure
  • Experience in configuration management (Puppet, Chef, or Ansible)
  • Description

    You will be responsible for the stream processing platform used for analytics and machine learning of worldwide Siri events. We process a triple digit billion events per day. To run our environment efficiently, we drive for proper monitoring, alerting and automation. The team’s goal is to ensure the reliability and performance at the highest level.As a member of the AIML Data Infrastructure Stream Processing Team, your responsibilities include: Manage one of Apple’s largest infrastructure supporting hundreds of millions of Siri customersDiagnose, fix, improve, and automate complex issues across the entire stack to ensure maximum uptime and performanceTake part in designing and building out our next generation realtime data processing infrastructure and push our services to the next levelHarden and launch new data models and data pipelines in productionEstablish SLA’s for all data sets and applications running in productionAdvise other teams (within and outside of Siri) on proper integration of our platformBuild relationships with Data Scientists, Product Managers and Software Engineers to understand data needsManage the infrastructure which powers ETL, Analytics, and Privacy Efforts within AIML

    Education & Experience

    BS, MS, or PhD degree in Computer Science or equivalent and 5+ years experience in data technologies

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