Developing ML applications in a safety-critical context is different from developing ML applications for non-safety use-cases. In the automotive industry, development standards, robustness of neural networks, and traceability from requirements to model development play a significant role. Although the use of these methods might be overkill in some situation for your ML application, I believe that other ML use-cases can still learn a few things from our approach to ML development for your own projects.