Ai Developer Technology Engineer Interview Questions

1,227 ai developer technology engineer interview questions shared by candidates

HR: CV, curriculum scolastico, esperienze lavorative, RAL e inquadramento contrattuale. Tecnico: praticamente tutto quello che potete pensare su AI act, NIS e DORA, ripeto tantissime domande sia generali sia specifiche. Esempio: tutta la timeline di implementazione dell'ai act nel dettaglio.
Jul 3, 2025

HR: CV, curriculum scolastico, esperienze lavorative, RAL e inquadramento contrattuale. Tecnico: praticamente tutto quello che potete pensare su AI act, NIS e DORA, ripeto tantissime domande sia generali sia specifiche. Esempio: tutta la timeline di implementazione dell'ai act nel dettaglio.

Q: What is the difference between supervised and unsupervised learning? Q: What is the hardest part of preparing a Machine Learning project? Q: How do you determine layer sizes in a Convolutional Neural Network? Q: What sort of applications would a CNN be used for?
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AI ML Intern

Interviewed at Intel Corporation

3.9
Jul 28, 2021

Q: What is the difference between supervised and unsupervised learning? Q: What is the hardest part of preparing a Machine Learning project? Q: How do you determine layer sizes in a Convolutional Neural Network? Q: What sort of applications would a CNN be used for?

How do you scale a LLM microservice if it has 10min cold start up time? How to load balance LLM service? How to scale up high servicec load? Whats the difference between ... and rerank? Explain why and how NN activation maps in consume GPU memory. Explain activation functions and its function in FFNs. What is LORA? How do you decrease model size (Quantization, etc)? How do you decide to shift to more complex model architecture (how do you evaluate that the simpler model reached its max capability)? More questions I don't remember
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AI LLM Engineer

Interviewed at Deutsche Telekom

3.8
Jul 2, 2025

How do you scale a LLM microservice if it has 10min cold start up time? How to load balance LLM service? How to scale up high servicec load? Whats the difference between ... and rerank? Explain why and how NN activation maps in consume GPU memory. Explain activation functions and its function in FFNs. What is LORA? How do you decrease model size (Quantization, etc)? How do you decide to shift to more complex model architecture (how do you evaluate that the simpler model reached its max capability)? More questions I don't remember

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