Vision Systems Architect

Job description

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.