NCNN Jobs in Computer Vision
Browse CV roles that require NCNN across all industries and experience levels.
0 open positions
Open Positions
What is NCNN?
NCNN is Tencent’s high-performance neural network inference framework for mobile and embedded platforms, written in C++ with no third-party dependencies. It is optimised for ARM CPUs and is popular where binary size, startup time and dependency-freedom matter.
Where NCNN is used
Mobile applications and embedded devices, particularly in markets where lightweight, dependency-free deployment on a wide range of ARM hardware is a priority.
Roles that ask for NCNN
- Mobile AI Engineer
- Embedded Vision Engineer
- Edge AI Engineer
- C++ Engineer, ML
- Computer Vision Engineer
Related skills & tools
NCNN jobs — common questions
Why choose NCNN over TFLite?
Smaller binaries, no external dependencies, strong hand-optimised ARM NEON kernels, and a permissive licence. TFLite has broader ecosystem support and better accelerator delegates, so the choice usually turns on binary size and platform coverage.
How do models get into NCNN?
Usually via ONNX, then through the conversion tools into NCNN’s param and bin format. Operator coverage is good for common vision architectures but custom layers need manual implementation.
How widely is it requested in job listings?
It is a niche skill, most visible in mobile-first companies and in the Asian market. Where it does appear it is usually alongside broader embedded and C++ optimisation experience.