Vision Systems Architect

Project Description:

• Owns the end-to-end vision and AI architecture for consumer devices. Defines scalable, power-efficient, and production-ready imaging and perception systems across product lines. Drives technical direction across sensor, ISP, CV, ML, and platform integration.

Responsibilities:

• Define and own end-to-end vision system architecture (sensor → ISP → CV/ML → application layer).

• Translate product and UX requirements into scalable technical solutions.

• Define image quality strategy aligned with AI and user experience goals.

• Architect reusable, modular CV/ML frameworks across multiple product SKUs.

• Drive system-level trade-offs across performance, power, cost, and thermal limits.

• Define AI model lifecycle strategy from training to OTA deployment.

• Architect heterogeneous compute utilization (CPU/GPU/NPU/DSP).

• Define system KPIs: latency, FPS, power, memory, boot time, and robustness.

• Lead technology selection for inference engines, frameworks, and hardware platforms.

• Guide SoC bring-up and performance validation for vision pipelines.

• Establish coding standards, modularization strategy, and long-term maintainability.

• Identify technical risks early and define mitigation strategies.

• Collaborate with hardware, ISP, Android/Linux platform, and product teams.

• Mentor senior engineers and provide architectural governance.

• Contribute to long-term vision/AI roadmap across product generations.

Mandatory Skills Description:

• Bachelor's or Master's degree in Computer Science, Electrical Engineering, or related field (PhD preferred).

• 10-15+ years of experience in imaging/vision/perception systems.

• Proven experience architecting and shipping multiple consumer products with vision/AI.

• Deep understanding of imaging pipeline (sensor behavior, ISP, tuning impact).

• Strong embedded system architecture experience.

• Expert-level C++ and system-level optimization knowledge.

• Strong expertise in CV and ML system integration.

• Experience deploying optimized ML models on consumer SoCs.

• Experience with heterogeneous compute architectures.

• Experience defining system-level KPIs and validation strategies.

• Strong cross-functional leadership and communication skills.

Nice-to-Have Skills Description:

• Experience with computational photography pipelines.

• Experience in AR/VR or advanced camera features.

• Experience with silicon bring-up and HW/SW co-design.

• Experience with large-scale model deployment and OTA updates.

• Experience in multi-camera or depth-sensing systems.

• Contributions to patents or technical publications.

• Experience leading architecture across multiple product generations.