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Apple AIML - Senior Applied Research Lead Health AI 
United States, Washington, Seattle 
823840485

06.06.2024
Description
In this role, you will use your skills and experience in ML and deep learning to design, implement and evaluate new machine learning models and algorithms to solve ambitious problems involving unique data and objectives. You will have the opportunity to explore and develop generative AI technologies. The successful candidate should possess excellent interpersonal skills and ability to work multi-functionally to transform novel research at the intersection of Health and ML into customer features.
Key Qualifications
  • 5+ years experience in hands-on experience in state-of-the-art machine learning and deep learning as applied to large-scale datasets
  • Strong background in generative models, natural language processing, and large language models
  • Proficiency developing large scale models using modern machine learning packages (e.g. TensorFlow, PyTorch, Jax)
  • Passionate about applying machine learning methods to deliver end-user experiences in health space
  • Experience in leading a team and track record of multi-functional collaboration to deliver customer-facing features in production
Education & Experience
Ph.D. in Computer Science, Machine Learning, or related fields or equivalent qualification.
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 $189,800 and $346,300, 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.