Vision Systems Architect

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. - 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.