Your question is Designing an Embedding Model. 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).
What are the key considerations when designing an embedding model for a specific application?
Discuss how you would define the embedding objective, collect and preprocess representative training data, choose a base architecture, and select an appropriate fine-tuning strategy. Explain how you would handle domain vocabulary, hard negatives, embedding dimension, latency, storage, and privacy. Include a practical evaluation plan using task-specific retrieval or similarity metrics, baselines, and error analysis. Your answer should distinguish general-purpose embeddings from application-specific embeddings and explain when fine-tuning is justified.
