Machine Learning Engineer
Apple · San Diego, CA · Hardware
About this role
Apple is hiring a mid-level Machine Learning Engineer based in San Diego, CA. The posting calls out experience with Python, LLMs, Data Structures, Machine Learning. Listed education preference: a bachelor's degree or equivalent.
- Role
- Machine Learning Engineer
- Function
- machine learning
- Level
- mid
- Track
- Individual contributor
- Location
- San Diego, CA
- Education
- Bachelor's degree
- Department
- Hardware
- Posted
- Apr 9, 2026
Job description
from Apple careersApple’s Health Sensing team is seeking a versatile Machine Learning Engineer to develop next-generation health algorithms that deliver meaningful insights to users by combining classical ML, signal processing, and emerging generative AI techniques. Our team has delivered impactful features including heart rate notifications, ECG, blood oxygen, sleep apnea notifications, and overnight vitals to millions of Apple Watch users.
This role is ideal for an engineer who enjoys moving quickly from idea to prototype to product, creatively overcoming data limitations, and applying new tools to multi-modal sensor fusion problems in health and wellness. You will work across the full algorithm lifecycle including data strategy, modeling, evaluation, optimization, and deployment.
<h3>Minimum Qualifications</h3>Bachelors degree in Computer Science, Electrical Engineering, Biomedical Engineering, Statistics, Applied Mathematics, or related field, or equivalent industry experience.
Strong foundation in machine learning, statistics, signal processing, or applied mathematics for real-world sensing problems
Experience applying modern AI techniques, including generative AI and agentic AI, to accelerate algorithm development, data generation, and performance evaluation
Proficiency in Python for algorithm development and optimization
Demonstrated ability to rapidly prototype, evaluate multiple approaches, and iterate based on experimental results
Experience owning algorithm development from early exploration through validation and integration
<h3>Preferred Qualifications</h3>Experience developing algorithms for physiological sensing using multi-modal data
Familiarity with on-device ML frameworks or resource-constrained optimization
Experience working with incomplete, noisy, or limited datasets
Background in experimental design and statistical validation
Experience with distributed or cloud-based ML workflows
Experience accelerating development through simulation, synthetic data, or creative data augmentation approaches
Self-driven, curious engineer comfortable taking ambiguous sensing problems from concept to working solutions