Health Sensing ML Engineer

Benefits

Parental leave

Not verified

Non-birth-parent leave

Not verified

Family-building benefits

• Fertility benefits: Not verified
• Adoption assistance: Not verified
• Surrogacy assistance: Not verified

Mental health support

Not verified

Relocation assistance

Not verified

Childcare support

Not verified

Learning budget

Not verified

Verification

Not verified last checked Jun 13, 2026

Salary

Not verified not verified - source not recorded; timestamp not recorded

401(k) match

Listed Source: EMPLR_CONTRIB_INCOME_AMT. source Last checked Jun 13, 2026.

Was this benefit information wrong? Tell us.

Schedule

Shift type

Not verified

Weekend work

Not verified

Application

Cover letter

Not verified

Assessment

Not verified

Deadline

Not stated

Where they hire

State eligibility is not yet verified.

About this role

Health Sensing ML Engineer Cupertino, United States of America 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 SW & Prototyping team, we develop algorithms for a variety of health sensors, including PPG, accelerometer, ECG. In this role, you will be at the forefront of developing ML algorithms for health sensing applications and ensuring the efficient evaluation of these models to be in production at scale. You will interact closely with ML engineers, clinicians, software and hardware engineers. You will deliver solutions on time and with high quality standing up to the standards of a customer facing product. 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 setting up data pipelines to model evaluation Analyze model behavior and finding weaknesses; drive design decisions with in-depth failure analysis Build end-to-end pipelines that prioritize rapid iterations in support for reliability of a complex multi-year projects Work multi-functionally to bring algorithms to real-world applications; this can span a wide range of partnerships with clinical authorities and engineering specialists across HW and SW Minimum Qualifications: BS in Computer Science, Engineering, Information Systems, or related technical field and a minimum of 3 years of equivalent experience Proven experience in developing machine learning and

Read the full description at jobs.apple.com. FewerJobs shows a source-linked preview and links to the original posting.