Data Infrastructure team within the Siri organization powers analytics, experimentation and ML feature engineering to power Siri we all love in our Apple devices. The mission of the Data Infrastructure org is to provide our engineers and data scientists a cutting edge, reliable and easy to use infrastructure for ingesting, storing, processing and interacting with data and ultimately help the teams that build data intensive applications be successful. You will work with many cross functional teams and lead the planning, execution and success of technical projects with the ultimate purpose of improving Siri experience for Apple customers. We are looking for engineers who want to bring their passion for infrastructure to build world class infrastructure products.
Are you a passionate about building scalable, reliable, maintainable infrastructure and solving data problems at scale? Come join us and be part of the Data Infrastructure journey.
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 teams 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 Apples largest infrastructure supporting hundreds of millions of Siri customers
* Diagnose, fix, improve, and automate complex issues across the entire stack to ensure maximum uptime and performance
* Take part in designing and building out our next generation realtime data processing infrastructure and push our services to the next level
* Harden and launch new data models and data pipelines in production
* Establish SLAs for all data sets and applications running in production
* Advise other teams (within and outside of Siri) on proper integration of our platform
* Build relationships with Data Scientists, Product Managers and Software Engineers to understand data needs
* Manage the infrastructure which powers ETL, Analytics, and Privacy Efforts within AIML
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