Description
The Platform Architecture systems prototyping team creates "livable prototypes": complete hardware and software product concepts that you can actually hold, interact with, and use in daily life, as opposed to isolated concept demonstrations. We are a small team of fearless, self-motivated, and curious generalists who love to make thoughtful, ambitious new things. In this role, you will build end-to-end prototype systems from initial whiteboard sketches to working devices. Depending on the project, you might spend one week integrating custom sensors, edge compute modules, and real-time audio/video streams, and the next week wiring up local and cloud AI models or building an interactive user interface. Collaborating with hardware, silicon, software, and ML partners across Apple, you will combine technologies in new ways. Your curiosity will drive you to learn whatever you need to turn bold ideas into reality.
Minimum Qualifications
BS degree in CS, CE, EECS, or a related engineering discipline (or equivalent industry experience) Experience designing and building software and computer systems Experience programming in one or more systems or application languages such as Swift, Rust, Python, C, C++, Go, or TypeScript Experience developing or integrating AI/ML models and services into software applications Experience interfacing software with hardware devices, sensors, or embedded platforms
Preferred Qualifications
10+ years industry experience MS or PhD in Computer Science, Computer Engineering, Artificial Intelligence, Human-Computer Interaction (HCI), or a related technical field Experience building applications with modern AI/ML capabilities (e.g., on-device or cloud LLMs, voice/audio processing, computer vision, or agentic workflows) Hands-on familiarity with embedded systems, edge devices (Apple platforms, NVIDIA Jetson, Raspberry Pi, microcontrollers), and hardware interfaces (e.g., I2C, SPI, UART, Serial, USB) Experience working across the full stack, from backend services and system software up to web or native UIs (e.g., React, TypeScript, WebGL, or SwiftUI) Track record of quickly learning unfamiliar hardware, software, and physical domains to solve complex problems