Банк вопросов из реальных собеседований

In invoice parsing, some documents are native PDF, some are scans. How do you determine which processing path to use and what errors to expect?

How to embed a ML reranker into an existing search if candidate generation already returns itemIds?

Article searches can be evaluated offline, but it is important for the product whether it helped the user. What online signals show this?

After launching the CV model at real points, errors, new dishes and new shooting conditions appear. How to build support and additional training?

What ways do Transformer order tokens exist and how does RoPE work?

The user writes a natural query to a large corporate database. How to match entities, abbreviations, tables and columns?

The photo shows the organization's sign. How to build a pipeline that extracts text and uses it in a product?

How to store a production plan extracted from documents so that new reports correctly update forecast features?

Why might a model based on historical production be dramatically wrong if a company invests in a new mining method or mine expansion?

It is necessary to forecast quarterly production by mine. What features and baseline model should be built before the LLM layer?

Explain at a high level how TensorRT or similar inference optimizers speed up neural networks, and why INT8 quantization usually needs calibration.

For international search, you can translate an existing description or generate a new one in the target language. How to compare approaches?

Why do VAD and diarization matter in an operator-client call pipeline, and how would you use them before ASR and extraction?

How would you integrate VLMs, image search, and a chat assistant into a real-estate search product so that they complement the core retrieval/ranking system instead of replacing it?

How does the model generate text token by token and what work saves the cache of keys and attention values?

A product transcribes medical consultations and uses an LLM for summarization and clinical notes, but the general model confuses medical terms. How would you improve domain understanding?

You need to build a system that searches for internal documents and helps answer questions. Which Pipeline should I design?

How are the Transformer encoder and decoder, self-awareness mechanism, Q/K/V, positional coding, and how do the GPT and BERT architectures differ from each other?

What blocks does a language model agent consist of, where is its state stored, and how does it safely invoke external tools?

What blocks does a language model agent consist of, where is its state stored, and how does it safely invoke external tools?

How to decompose the real-time CTR panel into event ingestion, streaming aggregation, storage and API?

How does the BERT bidirectional encoder differ from the GPT causal decoder and why are these architectures suitable for different tasks?

We need to make a block of recommendations in the basket for 10 million users and 100,000 products. How to build a simple basic version of the statistics of joint purchases?

How to safely roll out a new version of the ONNX model in production: what checks to do before release, how to enable traffic, what to monitor and how to quickly rollback?