# AI/ML developer workflow
Source: [https://docs.qualcomm.com/doc/80-70015-15B/topic/aiml-developer-workflow.html](https://docs.qualcomm.com/doc/80-70015-15B/topic/aiml-developer-workflow.html)
Join us and watch this training session focused on the Qualcomm Linux AI Developer Workflow.
It is tailored for developers and professionals in the IoT sector who are keen to enhance their understanding and skills in deploying on-device AI solutions.
The AI/ML developer workflow on Qualcomm Linux has two major steps:
| Step 1
Compile and optimize a model |
Compile and optimize the model from the third-party AI framework to efficiently run on Qualcomm hardware. For example, a Tensorflow model can be exported to a TFLite model.
Optionally, quantize, fine-tune performance, and accuracy using hardware-specific customizations.
|
| --- | --- |
| Step 2:
Build an application to use the optimized model to run on device inference |
Integrate the AI model into the use case pipeline.
Cross-compile the application to generate an executable binary using dependent libraries.
|
Last Published: Jan 21, 2026
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