Real-Time Computer Vision Architect

The Video Computer Vision and Video Engineering teams are centralized applied research and engineering organizations responsible for developing real-time on-device Computer Vision, Machine Perception, and Image Quality technologies for Apple products. We balance research and product development to deliver Apple quality, state-of-the-art experiences. We innovate across the full stack and partner with hardware and software teams to influence SW architecture, sensors, silicon, and PD/ID roadmaps that bring our vision to life.

The Architecture team within our organization is responsible for bringing together computer vision algorithms, firmware, and low-level software teams to drive some of the most exciting programs across many Apple products! We do this by enabling the co-design of computer vision algorithms and systems through a deep understanding of the complexities and trade-offs between algorithm performance, imaging pipeline, system resources, and real-time constraints. To be successful in this role, you not only have to be an excellent engineer, but also a phenomenal collaborator—comfortable communicating with a wide range of experts and leaders across many different domains, from firmware and OS to feature and experience. Are you ready to be a part of the next big thing at Apple?

Minimum Qualifications

• BS in Computer Science, Electrical Engineering, or other relevant fields with a minimum of 10 years relevant, proven experience.
• Validated ability to work in a highly multi-functional environment at the intersection of Computer Vision, Embedded Systems, ISP, Mechanical and Electrical Engineering, Optical Science, Human Factors or similar.
• Proven track record in developing and improving CV perception algorithms and ISP pipelines.
• Demonstrated experience in optimizing computer vision algorithms for performance, power, and memory on embedded platforms. Familiarity with firmware integration, operating system constraints, power and memory constraints, and low-level software development for image signal processing (ISP) in real-time applications.
• Strong understanding of perception sensing technologies including color and monochrome cameras, depth sensors, and IMUs. Ability to understand and articulate trade-offs between multiple sensing solutions and their impact on both high-level algorithms and low-level system performance.
• Depth of expertise in one or more computer vision specialty areas relevant to this role. These areas may include SLAM, tracking, classification, calibration, PnP-based pose estimation, scene understanding, human representation, and image enhancement.

Preferred Qualifications

• Breadth of knowledge in some areas of computer vision including either classical methods or ML. These areas may include SLAM, tracking, classification, calibration, PnP-based pose estimation, scene understanding, human representation, and image enhancement.
• Experience in translating ambiguous, high-level product goals into detailed feature-level architectures and system requirements. Proven ability to derive defensible end-to-end requirements at the system level and decompose them into module/component-specific requirements that include firmware, ISP, and OS constraints.
• Strong leadership skills to drive large multi-functional efforts, resolve conflicts, and present results to the highest levels of Apple leadership. Demonstrated ability to bridge the gap between high-level algorithm design and low-level system optimization—including the challenges of optimizing ISP performance under tight power and latency constraints.
• Experience in optimizing and fine-tuning ISP pipelines, including tasks like noise reduction, color correction, demosaicing, and dynamic range enhancement.
• Ideal candidates will also have exposure to modern innovative techniques including vision transformers, foundation models, and vision-language models, with a focus on integrating these methods into resource-constrained environments.
• Proficiency in debugging and optimizing performance at the firmware or OS level, with specific expertise in tuning ISP performance to ensure tight integration between hardware capabilities and algorithmic performance.