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.
SKILLS
Must have
- 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
• 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.
