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.
