Multimodal and Generative ML Engineer - Health Sensing

Cupertino, California, United States


Role Number:200546475
The Health Sensing team builds outstanding technologies to support our users in living their healthiest, happiest lives by providing them with objective, accurate, and timely information about their health and well-being. As part of the larger Sensor SW & Prototyping team, we take a multimodal approach, using a variety of sensors across HW platforms, such as camera, PPG, and natural languages.


In this role, you will be at the forefront of developing, evaluating and improving multimodal and generative models for real-world health/wellbeing applications on their objective quality and alignment with human intent and perception, such as truthfulness, adaptability, and model generalizability. You will work on data and evaluation pipeline of both human and synthetic data for model evaluation, leverage ML technologies such as reinforcement learning with human feedback and adversarial models.

Minimum Qualifications

  • Enhance multimodal capabilities and adapt pre-trained models for new tasks
  • Work across the entire ML development cycle, such as developing and managing data from various endpoints, managing ML training jobs with large datasets, and building efficient and scalable model evaluation pipelines
  • Analyze model behavior, identify weaknesses, and drive design decisions with failure analysis. Examples include, but not limited to: model experimentation, adversarial testing, creating insight/interpretability tools to understand and predict failure modes
  • Collaborate with algorithm engineers to build reliable end-to-end pipelines for long-term projects
  • Work cross-functionally to apply algorithms to real-world applications with designers, clinical experts, and engineering teams across HW and SW
  • Ability to independently run and analyze ML experiments for real improvements

Key Qualifications

Preferred Qualifications

  • Expertise in deep learning (e.g. hands-on training and evaluation experience with transformers)
  • Experience incorporating multiple modalities into large language models (LLMs)
  • Proficiency in Python and ML frameworks (e.g., PyTorch, TensorFlow)
  • Ability to write clean, performant code and collaborate using standard software development practices

Education & Experience

BS and a minimum of 3 years relevant industry experience

Additional Requirements

Pay & Benefits

  • 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. Learn more about your EEO rights as an applicant.