Your question is Choosing Domain Embeddings. 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).
How do you select the appropriate embeddings model for a domain-specific dataset?
Explain a practical selection process rather than naming one universally best model. Address corpus inspection, candidate-model comparison, preprocessing, domain adaptation, retrieval-oriented evaluation, out-of-vocabulary behavior, latency, memory, licensing, and production monitoring. Include a small Python experiment that compares at least two embedding models on representative domain text.