In-depth questions about transformers and their architecture Discussion on LLM fine-tuning techniques and challenges Basic machine learning concepts (supervised vs unsupervised learning, regularization) Practical scenario: designing a system to categorize customer support tickets Questions about my past projects and experience with model deployment Brief discussion on AI ethics and bias mitigation
Parle-nous du projet ML où tu as eu le plus d'impact
question was about networking in Sub-Netting
Why this role, past experiences, and skills
Tell me about a time you had a very big professional failure. How did you handle it? Was a customer involved? How did you communicate the failure to the customer?
1. Motivare la scelta del mio percorso di studi 2. Parlare di una volta che ho avuto una difficoltà e come la ho superata 3. Come mi organizzo quando devo gestire più attività parallelamente 4. Cosa mi aspetto dall'esperienza di tirocini 5. Parlare di me
Q. A case was given and I had to select an appropriate ML algorithm to deal with it and explain my approach.
Please explain what are transformers? And difference between llm in poc stage and deployment
They asked questions mainly on DSA concepts including loops, lists, graphs, and linked lists.
parsing json data from a long string Explain positional encoding in transformer. Build the most optimized prompt generation pipeline - data, labeling, ML models, features etc
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