Computer Vision Systems Engineer

What you'll do

• Lead system- and algorithm-level architecture definition to drive hardware and software requirements.
• Profile and optimize algorithm and model performance across memory, compute, power, and bandwidth constraints.
• Develop and deploy production-quality computer vision and video processing algorithms on mobile and embedded platforms.
• Write technical documentation, design specifications, and feature descriptions for internal teams and external partners.
• Provide technical mentorship and guidance to engineers across various experience levels.
• Influence technical decisions and system-level architecture for key products and organizational goals.
• Use performance profiling tools and hardware simulators to optimize on-device AI deployment.

What we're looking for

• Hold a Bachelor's degree with 2+ years of relevant experience, a Master's degree with 1+ year of experience, or a PhD in a related field.
• Possess a strong background in computer vision and video processing algorithms.
• Demonstrate a solid understanding of SoC architecture, including compute accelerators, memory hierarchies, and hardware/software interfaces.
• Have hands-on experience with modern deep learning architectures.
• Possess strong coding skills in Python and C/C++ for production-quality development and optimization.
• Experience using ML/CV frameworks such as PyTorch, TensorFlow, ONNX, and OpenCV.
• Have experience with real-time computer vision systems or embedded AI deployment.
• Experience with hardware modeling, FPGA prototyping, or RTL design (preferred).