Core OS Applied ML Engineer

Santa Clara Valley (Cupertino), California, United States
Software and Services

Summary

Posted:
Weekly Hours: 40
Role Number: 200070242
Are you excited about the ways intelligence can make your battery last longer or your apps launch faster? Handling resource consumption and contention is a key differentiator for Apple products and the Core OS Dynamic Resource Management team focuses on solving these key resource tradeoff problems. By imbuing the low layers of the operating system with intelligence, we can maximize the user experience within our constraints of battery life, thermals, memory, network usage, and many other factors. The team is looking for extraordinary candidates to design and implement innovative software to manage process runtime and other resource usage on all products across our multiple software platforms. In this unique and highly visible role, you will be at the center of optimization efforts for handling system resources, influencing and assisting cross-functionally with the adoption of novel operating system concepts. Through data analysis, ML model development, and on-device deployment of these models you will push the boundary of what's possible at the core of the operating system.

Key Qualifications

  • Strong programming background
  • Clear understanding of operating system components and responsibilities
  • Familiarity with statistics, data analysis, or machine learning and the enthusiasm to learn more Highly professional and collaborative with outstanding communication and presentation skills Proven track record leading software projects from inception through customer delivery
  • Ability to deliver high quality work on tight schedules consistently

Description

• Design, implement, optimize, and evangelize new operating system constructs to enable intelligent resource management • Analyze, understand, and present key performance data for highly-visible OS features • Write elegant, performant code in Objective-C or Swift and test, debug, and productize it • Rapidly prototype new ideas and features in collaboration with others • Deploy models in resource-constrained environments, optimizing inference performance where necessary • Consult with and influence other teams to drive adoption of new APIs

Education & Experience

BS in Computer Engineering or equivalent experience

Additional Requirements