Senior Machine Learning Engineer - System Exper...
@ Apple

California, United States
$200,000
On Site
Full Time
Posted 22 hours ago

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About the Role

The Senior Machine Learning Engineer - System Experience Personalization at Apple will help make iOS more intelligent, proactive, and personal. You will develop on-device intelligence solutions and machine learning models that power features such as personalized notifications, smart widget stacks, and app predictions for millions of users.

Key Responsibilities

  • Collaborate with talented Software and ML engineers across Apple.
  • Design, architect, and implement innovative ML solutions on iOS.
  • Develop machine learning models under power and performance constraints.
  • Work with large scale, real world datasets for classification, ranking, and recommendations.
  • Provide technical leadership and ensure high quality features.

Minimum Qualifications

  • M.S. or PhD in Machine Learning, Computer Science or related field.
  • 5+ years of proven experience building machine learning systems.
  • Comprehensive understanding of ML algorithms, deep learning architectures and various modeling techniques.

Preferred Qualifications

  • Experience in resource constrained computing and mobile development.
  • Strong foundation in Computer Science fundamentals and software engineering best practices.
  • Proficiency with machine learning libraries such as TensorFlow, Scikit-learn, PyTorch, or similar.

Key Skills/Competency

  • Machine Learning
  • Deep Learning
  • On-Device Intelligence
  • iOS Development
  • Software Engineering
  • Data Analysis
  • Algorithm Design
  • Privacy
  • TensorFlow
  • PyTorch
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How to Get Hired at Apple

🎯 Tips for Getting Hired

  • Tailor your resume: Highlight ML and iOS expertise.
  • Research Apple's culture: Understand their privacy and innovation commitment.
  • Showcase projects: Emphasize on-device ML implementations.
  • Prepare for technical interviews: Review ML algorithms and system design.

📝 Interview Preparation Advice

Technical Preparation

Review ML algorithms and deep learning fundamentals.
Practice on-device model optimization techniques.
Experiment with TensorFlow and PyTorch projects.
Study resource constrained computing in mobile contexts.

Behavioral Questions

Describe a time you led a project.
Explain how you handle tight deadlines.
Discuss a challenging problem solved collaboratively.
Share experience adapting to new technology quickly.

Frequently Asked Questions