Your question is Model Optimization Techniques. Take a moment with it on the right.
Talk me through your thinking if you like. When you're confident, submit your answer and I'll grade it like a real screen (7/10 or better passes).
You are comparing several candidate models for a supervised learning task and want to improve performance without overfitting. The team needs a principled way to tune the model and decide when a change is actually better.
What is your experience with machine learning model optimization techniques?