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Generative AI & Multimodal Models
AI/ML & Deep Learning

Vision-Language Models & Multimodal AI

TechnicalHard~30 minDesigned by experts

About this interview

A technical interview on Generative AI & Multimodal Models, pitched at the hard level. A voice AI interviewer leads the conversation, adapts its questions to your answers, keeps you on topic, and afterward gives you honest, specific feedback on where you were strong and where to improve. Expect roughly 30 minutes.

What you'll be assessed on

Explain CLIP/SigLIP contrastive pretraining and why it produces strong zero-shot visual representations
Describe the ViT encoder-projector-LLM architecture used in models like LLaVA and PaliGemma
Compare early vs late fusion and cross-attention fusion approaches in multimodal models
Distinguish VLMs from Vision-Language-Action models and explain how VLAs enable robotic control

Topics covered

CLIP / SigLIP contrastive pretrainingViT encoder-projector-LLM architectureEarly vs late fusion and cross-attention fusionVLMs vs VLAs and robotic control

A few sample questions

Just examples to set expectations - the real interview has many more and adapts to your responses.

What does CLIP stand for, and at a high level, what problem was it designed to solve?
PaliGemma uses SigLIP as its vision encoder rather than a CLIP-style encoder. What advantage does that give it for tasks like document understanding and OCR?
What kinds of tasks can a modern VLM handle, and which tasks still challenge it — give three examples on each side.

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