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Al colloquio personale mi sono state poste domande molto comuni ai colloqui di lavoro: come per esempio "perché hai deciso di cambiare lavoro?", "come hai gestito situazioni di difficoltà nel tuo attuale ambiente lavorativo?", "dove ti vedi tra 5/10/20 anni?". Mentre ai colloqui successivi mi hanno posto domande più pratiche, quindi abbiamo simulato un role play dove dovevo convincere chi mi faceva il colloquio a partire con EF.
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Language Consultant

Interviewed at EF (Education First)

3.4★
Feb 11, 2024

Al colloquio personale mi sono state poste domande molto comuni ai colloqui di lavoro: come per esempio "perché hai deciso di cambiare lavoro?", "come hai gestito situazioni di difficoltà nel tuo attuale ambiente lavorativo?", "dove ti vedi tra 5/10/20 anni?". Mentre ai colloqui successivi mi hanno posto domande più pratiche, quindi abbiamo simulato un role play dove dovevo convincere chi mi faceva il colloquio a partire con EF.

Technical Assessment (20 minutes) LeetCode Question: Longest Palindromic Substring Coding live where the interviewer can see your code on a shared editor. Discussion and Questions (40 minutes) Self-Introduction Project Discussion: Explain a project related to LLM LLM Creation: How is a Large Language Model created? Model Architectures: Explain the different models and their architectures (e.g., GPT, LLAMA, Falcon, BLOOM) Positional Embeddings: What is the purpose of positional embeddings? Normalization Techniques: Difference between BatchNorm and LayerNorm Retrieval-Augmented Generation (RAG): - What is RAG? Explain its purpose. - Even if you use RAG, there are hallucinations occurring. Why is this so and what can you do to mitigate? - What other current academic advancements in RAG? Explain about some frameworks that are trending. Scenario Question: If we have large-scale data (billions of records) from the web, how can I efficiently select math-related data? Discuss using distributed computing frameworks if possible.
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Algorithm Engineer, Large Language Model

Interviewed at Shopee

3.7★
Nov 5, 2024

Technical Assessment (20 minutes) LeetCode Question: Longest Palindromic Substring Coding live where the interviewer can see your code on a shared editor. Discussion and Questions (40 minutes) Self-Introduction Project Discussion: Explain a project related to LLM LLM Creation: How is a Large Language Model created? Model Architectures: Explain the different models and their architectures (e.g., GPT, LLAMA, Falcon, BLOOM) Positional Embeddings: What is the purpose of positional embeddings? Normalization Techniques: Difference between BatchNorm and LayerNorm Retrieval-Augmented Generation (RAG): - What is RAG? Explain its purpose. - Even if you use RAG, there are hallucinations occurring. Why is this so and what can you do to mitigate? - What other current academic advancements in RAG? Explain about some frameworks that are trending. Scenario Question: If we have large-scale data (billions of records) from the web, how can I efficiently select math-related data? Discuss using distributed computing frameworks if possible.

Why do you want to work for OSCE, what do you know about it, your experience in translation/interpretation services- describe, describe a challenging translation experience, describe a situation where you have to translate opinions that are different from your own, and the last question was oral consecutive translation from one language to the second and reverse.
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Language Assistant

Interviewed at OSCE

3.8★
Sep 14, 2015

Why do you want to work for OSCE, what do you know about it, your experience in translation/interpretation services- describe, describe a challenging translation experience, describe a situation where you have to translate opinions that are different from your own, and the last question was oral consecutive translation from one language to the second and reverse.

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