Apple AR/VR Job | Generative AI Scientist - Health
Job（岗位）: Generative AI Scientist - Health
Citys（岗位城市）: Cupertino, California, United States
Date（发布日期）: 2025-1-23
Summary（岗位介绍）
The Health Sensing team builds outstanding technologies to support our users in living their healthiest, the happiest lives by providing them with objective, accurate, and timely information about their health and well-being. As part of the larger Sensor Software & Prototyping team, we take a multimodal approach using a variety of sensors across hardware platforms, such as camera, wearable sensors, and natural language!
Qualifications（岗位要求）
Deep technical expertise in machine learning and algorithm design, including at least one of: large language or multimodal model architectures, memory representation, planning, knowledge retrieval, natural language understanding, reinforcement learning.
Hands-on experience developing complex ML systems in an applied setting, including post-training techniques like supervised fine-tuning, adapter training, and reinforcement learning from human feedback.
Proficiency using python and deep learning frameworks (e.g. PyTorch) in a peer-reviewed environment
Strong communication skills, comfort working with multiple engineering teams on complex projects, and experience contributing to an inclusive team culture
Experience in building consumer digital health and wellness products
Description（岗位职责）
In this role, you will be at the forefront of developing, evaluating and improving generative models for real-world health/wellbeing applications! You will innovate on innovative techniques in planning, memory representation, and reinforcement learning with human feedback to develop generative systems that achieve the highest levels of quality, reliability, and alignment with human intent.
Additional Requirements（额外要求）
PhD in a field such as computer science, mathematics, statistics, and at least 3 years of proven experience
Experience applying a scientific approach to drive machine learning innovation: developing hypotheses, crafting experimentation strategies, and guiding data generation / collection (e.g. user studies, annotation workflows, A/B tests).
Knowledge of health informatics or experience with sophisticated health data sources (e.g. EHRs, medical ontologies, wearables)
Familiarity with privacy-preserving ML techniques
