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Apple Software Engineer Analytics & Applied ML United States, California, Cupertino 39577102
13.06.2024
Description
Design and deploy ML applications for optimized wireless experience on iOS products. Build scalable solutions to spark the potential of telemetry for data mining and anomaly & trend detection algorithms. Develop on device and crowd sourced learning frameworks to improve Wireless product experience. Deploy and maintain Machine Learning models on-device using tools like Core ML needed for cellular features. Use cellular product experimentation and A/B testing frameworks to validate machine learning model deployments. Design and develop Analytics module running on iOS that aggregates and correlates information across the cellular software stack.
Minimum Qualifications
- 5+ years of professional software engineering experience, ideally working on Applied Machine Learning
- Strong object-oriented programming experience in C++, Objective C or Swift
- Understanding of and passion for data analytics & product quality
- Experience prototyping and shipping customer facing features on embedded systems
- Experience with scalable & cross layer system design
Preferred Qualifications
- 8+ years of professional software engineering experience, ideally working on Applied Machine Learning
- Strong Understanding of Machine Learning Fundamentals
- Experience Delivering ML Powered Software Features/ Applications
Pay & Benefits
- At Apple, base pay is one part of our total compensation package and is determined within a range. This provides the opportunity to progress as you grow and develop within a role. The base pay range for this role is between $170,700 and $300,200, and your base pay will depend on your skills, qualifications, experience, and location.Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.
Apple is an equal opportunity employer that is committed to inclusion and diversity. We take affirmative action to ensure equal opportunity for all applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or other legally protected characteristics.
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