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Apple Machine Learning Scientist - Health Sensing 
United States, California, Cupertino 
145060334

29.06.2024
Description
Develop innovative algorithms for extracting insight from sensor and health data and optimizing performance using machine learning/deep learning on big data resourcesAnalyze and improve efficiency and stability of algorithms deployed to user devices
Minimum Qualifications
  • Bachelor's Degree
  • Excellent programing skills in relevant programming languages (e.g., Python), and machine learning frameworks (e.g., PyTorch or TensorFlow).
  • Experience with signal processing, machine learning, statistical analysis and scientific reasoning
  • Outstanding interpersonal and communication skills, able to communicate complex topics to people from a variety of backgrounds and adapt to different audiences
Preferred Qualifications
  • Master in BME/CS/CE/EECS/Math/Physics or equivalent
  • Experience with algorithm design for health sensing, knowledge of human physiology is a plus
  • Previous experience designing data collection studies, and analyzing data quality and usability
  • Hands-on experience with large scale data solutions with distributed data processing frameworks (e.g. MapReduce, Spark) and designing/optimizing scalable frameworks to run machine learning experiments
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 $138,900 and $256,500, 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.