OS Performance Engineer (AI Feature Performance)

Great performance is critical to Apple's product experience, but exceptional performance begins with the decisions we make today about the products of tomorrow. The Performance Modeling and Features team within CoreOS Performance serves as performance optimizers and strategic advisors across Apple's software and hardware organizations, using performance analysis, data-driven insights, and predictive modeling to improve performance, as well as shape architecture decisions, hardware specifications, and product planning. The team is seeking an engineer to focus on AI feature performance and can operate at a unique intersection: using performance expertise, data science, and strategic planning to not just measure and optimize performance, but model it, predict it, and use those insights to shape decisions. If this excites you, we should talk!

In this role, you'll serve as a performance optimizer and advisor with a focus on AI feature usage on our platforms, working with everyone from feature teams architecting new capabilities to hardware teams planning next-generation devices. Your goal will be to ensure Apple ships smooth, snappy, and efficient AI features and the best possible customer experience for the system as a whole. You'll write code for feature optimizations and testing automation, as well as analysis pipelines and simulation tools that enable teams to make informed decisions based on quantitative insights.

Minimum Qualifications

Bachelor's degree in Computer Science, Electrical Engineering, Statistics, Mathematics, or related quantitative field, or equivalent professional experience
Proficiency in programming languages for OS systems development, data analysis, and/or modeling (e.g., Python, R, SQL, C/C++ Objective-C, Swift)
Working knowledge of modern AI/LLM systems, AI/LLM model architecture, and operating system fundamentals (e.g., memory management, scheduling, file systems, storage)
Demonstrated ability to transform raw data into actionable insights through analysis, modeling, and visualization
Excellent problem-solving and critical-thinking skills
Strong written and verbal communication skills, with ability to explain technical concept to diverse audiences
Proven ability to collaborate effectively across teams and build relationships with diverse stakeholders

Preferred Qualifications

M.S. or Ph.D. in Computer Science, Electrical Engineering, Applied Mathematics, Statistics, or related quantitative field
Experience shipping high-performance modern LLM-based AI features
Experience with performance modeling, capacity planning, or computer architecture evaluation
Knowledge of modern CPU and memory architectures, and hardware/software interactions
Experience with performance analysis tools and methodologies (e.g.,profiling, tracing, instrumentation) Experience driving cross-functional projects and influencing decisions across diverse stakeholder groups
Track record of connecting quantitative insights to strategic product or business decisions
Prior experience in Unix, Linux, macOS, or iOS development or performance optimization