Prototyping Engineer

We are seeking a visionary Prototyping Engineer who operates at the bleeding edge of spatial computing, generative AI, and computational photography. In this role, you will not just build 3D environments; you will architect the simulated testing grounds for the next generation of Apple hardware. By blending the aesthetic sensibilities of visual effects and cinematography with modern AI-accelerated workflows, you will explore how emerging world models can redefine what a camera is capable of. Your work will directly inform hardware design, translating insights from high-fidelity simulations into concrete specifications for future sensors. You will tackle the defining challenges of embodied AI: making sense of chaotic physical environments, filtering noisy sensor data, and accurately interpreting user intent to create seamless, magical experiences. The ideal candidate possesses exceptional taste, deep technical rigor, and a relentless drive to accelerate their prototyping process using the latest AI development paradigms.BS and a minimum of 3 years relevant industry experience Demonstrated ability to accelerate software development and rapid prototyping by seamlessly integrating modern AI coding assistants and automation into your workflow Deep understanding of optical physics and real-world camera characteristics (e.g., motion blur, sensor noise, optical geometry, lens distortion) to ensure synthetic data and simulations accurately mirror physical hardware Strong foundation in real-time computer graphics and novel view synthesis, paired with a refined aesthetic eye for lighting, composition, and cinematographyMS or PhD in Computer Science, AI/ML, Computer Graphics, HCI, or a related technical discipline, with substantial applied research or industry experience Proven track record of designing robust systems that can interpret ambiguous user inputs and noisy sensor data within unpredictable, real-world conditions Passion for the frontier of spatial intelligence, with experience leveraging, fine-tuning, or developing foundation models specifically tailored for multimodal sensor data (camera, microphone, IMU, etc.) Demonstrated ability to bridge the gap between software and hardware, translating software-driven insights and AI simulations into actionable physical camera specifications Familiarity developing for the Apple ecosystem (Swift, Metal, RealityKit, visionOS) Hands-on experience with motion capture pipelines and the generation of high-quality synthetic 3D datasets for machine learning research Comfortable navigating the ambiguity of an incubation environment, with a talent for communicating complex technical tradeoffs across design, software, and hardware teams