Vector Databases Assessment

Online assessment to evaluate advanced vector search and similarity engineering skills

This assessment helps employers assess a candidate’s ability to design, manage, and optimize high-performance vector databases for AI applications. It covers advanced-level concepts such as indexing strategies, vector quantization, hybrid search integration, and metric selection. The test also evaluates candidates on performance tuning, scalability, and data security in vector-based systems. Ideal for AI infrastructure engineers and data platform specialists, this assessment identifies experts capable of implementing efficient and secure semantic search architectures. With instant scoring and detailed analytics, it enhances technical recruitment precision.

Sample Question

You are the Principal Data Engineer at a European e-commerce company that handles millions of product searches daily. Your recommendation engine, powered by FAISS, begins slowing down during concurrent updates, especially when sales campaigns are running. The CTO suspects a hardware bottleneck, while the DevOps team claims that constant re-indexing is the cause. Logs show multiple write operations overlapping with user queries, leading to temporary unavailability. The system must stay operational 24/7, and you have limited budget for scaling. You are asked to stabilise the pipeline without major rearchitecture. What should you prioritise to fix the issue effectively?