Computer Vision System Engineer

What you'll do

• Map state-of-the-art computer vision and deep learning models onto mobile AI accelerators and heterogeneous compute platforms.
• Drive architecture development for deep learning engines including dataflows, tensor processing pipelines, and quantization techniques.
• Analyze neural network workloads to identify architectural enhancements for performance, power efficiency, and memory bandwidth.
• Define HW/SW partitioning strategies across CPUs, GPUs, DSPs, NPUs, and dedicated accelerators.
• Develop workload characterization methodologies and performance models for computer vision and AI applications.
• Conduct top-down architecture exploration from algorithm requirements through hardware implementation projections.
• Define next-generation AI engine features based on evolving computer vision workloads and hardware constraints.

What we're looking for

• Bachelor's degree in Computer or Electrical Engineering, Computer Science, or related field and 2+ years of relevant work experience.
• Master's degree in Computer or Electrical Engineering, Computer Science, or related field and 1+ year of relevant work experience.
• PhD in Computer or Electrical Engineering, Computer Science, or related field.
• Strong understanding of mobile computer vision applications including object detection, tracking, segmentation, and computational photography.
• Expertise in system architecture and HW/SW partitioning for computer vision and AI workloads.
• Strong understanding of deep learning accelerator architectures, including tensor processing and neural network bottlenecks.
• Strong programming skills in C/C++ and Python with hands-on experience in algorithm prototyping and performance analysis.
• Multiple years of experience developing mobile computer vision and AI systems (preferred).