Design and implement advanced computer vision and image processing pipelines optimized for real-time consumer devices.
Collaborate with ISP, sensor, and tuning teams to optimize image quality for downstream AI and UX performance.
Develop and deploy ML models for visual recognition, enhancement, tracking, or scene understanding.
Optimize ML models for edge deployment (quantization, pruning, distillation, hardware-aware tuning).
Implement performance-critical algorithms in modern C++ for embedded platforms.
Optimize for latency, power consumption, memory footprint, and thermal constraints.
Integrate inference engines (TFLite, TensorRT, ONNX Runtime, etc.) on target SoCs.
Work closely with Android/Linux platform teams to integrate camera and AI pipelines.
Define and track KPIs: FPS, power usage, memory, startup time, and accuracy.
Profile and optimize performance across CPU/GPU/NPU/DSP.
Drive debugging of complex system-level issues in production builds.
Ensure robust unit testing and contribute to automated validation pipelines.
Mentor engineers and review architecture/design proposals.
Support product bring-up and mass production readiness.