Senior Software Engineer, Applied Machine Learning
The Applied Sensing & Health team delivers critical Health and Fitness features for Apple Watch, iPhones, and other Apple products. We are seeking a versatile software engineer who can bridge the gap between cutting-edge ML research and robust production systems. In this pivotal role, you will architect and implement complex C++ systems for sensor data processing, translate advanced ML research into optimized, high-performance production algorithms, analyze and visualize data to drive profound insights, and maintain sophisticated system software with multi-threading and real-time constraints.
Description
Your work will span from low-level systems programming to ML model implementation to deep data analysis-sometimes building sophisticated algorithms, sometimes crafting the critical infrastructure that makes everything work reliably at Apple's scale. You'll collaborate closely with ML engineers, scientists, and multi-disciplinary teams across the company, working throughout the entire software lifecycle to deliver best-in-class, performant, and reliable systems that impact millions of users daily..","responsibilities":"Strong proficiency in C++ or Objective-C/Swift development and debugging, with extensive experience in complex, multi-threaded and concurrent systems, including synchronization and debugging advanced threading issues.
Working knowledge of Python for ML model development, data analysis, and prototyping.
Solid understanding of ML pipelines, model implementation, and translating research prototypes into production code.
Familiarity with modern GenAI-enabled development workflows and tools (e.g., AI-assisted coding, automated code generation, intelligent debugging), coupled with a strong aptitude for learning and adapting to evolving technologies.
Want more jobs like this?
Get jobs in Cupertino, CA delivered to your inbox every week.
Comfort with data analysis and visualization, deriving actionable insights from sensor data.
Preferred Qualifications
A demonstrated passion for health and fitness, driven to empower users to live healthier, more active lives through technology.
Exceptional collaboration and communication skills, adept at driving cross-functional initiatives.
A proactive, inquisitive problem-solver who thrives on tackling complex challenges and delivering innovative solutions.
Demonstrated ability to consistently achieve results in dynamic and challenging environments.
Minimum Qualifications
MS or Ph.D. preferred in Computer Science, Electrical Engineering, or related field, plus 3+ years of software engineering experience with exposure to both systems programming and ML/data analysis domains.
Strong proficiency in C++ or Objective-C/Swift development and debugging, with extensive experience in complex, multi-threaded and concurrent systems, including synchronization and debugging advanced threading issues.
Working knowledge of Python for ML model development, data analysis, and prototyping.
Solid understanding of ML pipelines, model implementation, and translating research prototypes into production code.
Familiarity with modern GenAI-enabled development workflows and tools (e.g., AI-assisted coding, automated code generation, intelligent debugging), coupled with a strong aptitude for learning and adapting to evolving technologies.
Comfort with data analysis and visualization, deriving actionable insights from sensor data.
Apple is an equal opportunity employer that is committed to inclusion and diversity. We seek to promote 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 .
Perks and Benefits
Health and Wellness
Parental Benefits
Work Flexibility
Office Life and Perks
Vacation and Time Off
Financial and Retirement
Professional Development
Diversity and Inclusion
Company Videos
Hear directly from employees about what it is like to work at Apple.