Apple is looking for a versatile software engineer to bridge the gap between ML research and production systems for their Applied Sensing & Health team, which develops Health and Fitness features for Apple Watch, iPhones, and other Apple products. The goal is to architect and implement complex C++ systems for sensor data processing, translate ML research into optimized production algorithms, analyze and visualize data to drive insights, and maintain complex system software with multi-threading and real-time constraints.
Requirements
- strong proficiency in C++ or Objective-C/Swift development and debugging, particularly for complex, multi-threaded systems
- working knowledge of Python and are comfortable using it for ML model development, data analysis, and prototyping
- solid understanding of ML pipelines, model implementation, and can translate research prototypes into production code
- comfortable with data analysis and visualization, and can derive actionable insights from sensor data
- excel at systems-level programming including performance optimization, memory management, and real-time constraints
- architect robust system infrastructure while understanding the algorithmic requirements it needs to support
- experience with concurrent programming, synchronization, and debugging complex threading issues
Responsibilities
- architect and implement complex C++ systems for sensor data processing
- translate ML research into optimized production algorithms
- analyze and visualize data to drive insights
- help maintain complex system software with multi-threading and real-time constraints
- building sophisticated algorithms
- crafting the critical "plumbing" that makes everything work reliably at scale
- working throughout the software lifecycle to deliver best-in-class performant and reliable systems
Other
- MS or Ph.D in Computer Science, Electrical Engineering, or related field, plus 8+ years of software engineering experience with exposure to both systems programming and ML/data analysis domains
- appreciate both the engineering rigor of production systems and the analytical creativity of applied ML
- thrive in environments requiring versatility and enjoy switching between systems engineering, ML implementation, and data analysis
- thrive in a collaborative environment and can clearly communicate while driving multiple projects across teams
- obsessively passionate and inquisitive, and seek to solve everyday problems in innovative ways
