Senior Vision Systems Engineer
Project description
• hands-on technical leader responsible for designing, optimizing, and productizing high-performance computer vision and AI pipelines for consumer devices. This role ensures real-time performance, power efficiency, and production robustness across embedded platforms.
Responsibilities
- 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.
SKILLS
Must have
- Bachelor's or Master's degree in Computer Science, Electrical Engineering, or related field.
- 7-10+ years of experience in computer vision/image processing.
- Proven experience shipping at least one consumer product with embedded vision/AI.
- Strong C++ expertise (C++14/17/20), including performance optimization.
- Strong experience with OpenCV and ML frameworks (PyTorch, TensorFlow, ONNX).
- Experience deploying ML models on embedded/edge devices.
- Experience with model optimization (quantization, pruning).
- Strong understanding of 2D/3D geometry and linear algebra.
- Experience working on embedded Linux or Android systems.
- Strong debugging and performance profiling skills.
- Experience optimizing for power and thermal constraints.
Nice to have
• Experience with mobile SoCs (Qualcomm, MediaTek, Exynos, etc.). • Experience with CUDA / OpenCL / Vulkan / OpenGL ES / SIMD. • Experience with camera calibration and ISP interaction. • Experience building for Android Camera HAL or Yocto-based systems. • Experience with AR, computational photography, or video processing. • Experience with multi-camera systems. • Exposure to production validation and manufacturing constraints.
