Health Sensing ML Engineer — Wearables & Health Data

Apple Inc.; Cupertino (CA); On-site; USD 150,400 - 277,600; Full time

Job summary

Apple Inc. Cupertino seeks a ML Engineer for Health Sensing to develop ML models from health sensor data. You will collaborate with ML, software, hardware engineers and clinicians to deliver reliable, production-ready solutions at scale.

You will analyze health data, implement end-to-end ML pipelines, and drive design decisions through failure analysis, supporting multi-year projects with cross-functional teamwork.

Qualifications

• BS in Computer Science, Engineering, Information Systems, or related technical field.
• Proven experience in developing machine learning and deep learning models, preferably in health domain.
• Proficiency in Python and ML frameworks (PyTorch, TensorFlow).
• Experience with health data analysis, including time-series and sensor data.
• Data preprocessing, feature extraction, and model evaluation techniques.
• Familiar with software development standard methods and teamwork.
• Ability to run large ML training jobs on a distributed backend with large data volumes.

Responsibilities

• Develop and implement machine learning and deep learning models using health sensing data.
• Analyze large-scale health data from wearable sensors to extract significant insights.
• Work across the entire ML development cycle, from data pipelines to model evaluation.
• Analyze model behavior and drive design decisions with in-depth failure analysis.
• Build end-to-end pipelines for rapid iterations and reliability on long-running projects.
• Collaborate across hardware and software teams and with clinical authorities as needed.

Skills

Python

PyTorch

TensorFlow

Health data analysis

Time-series data

Distributed training

Data preprocessing

Education

BS in Computer Science or related field

MS or PhD or equivalent

Job description

Apple Inc. Cupertino seeks a ML Engineer for Health Sensing to develop ML models from health sensor data. You will collaborate with ML, software, hardware engineers and clinicians to deliver reliable, production-ready solutions at scale.

You will analyze health data, implement end-to-end ML pipelines, and drive design decisions through failure analysis, supporting multi-year projects with cross-functional teamwork.