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About this interview
A technical interview on Emerging Architectures & Research Trends, 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 Mixture of Experts (MoE) routing: sparse vs dense activation and why it improves parameter efficiency
Describe multimodal LLM architecture components: modality encoder, input projector, LLM backbone, and output projector
Explain test-time compute scaling: chain-of-thought sampling, process reward models, and MCTS variants
Explain model merging techniques (SLERP, TIES, DARE) and their use cases
Topics covered
MoE ArchitectureMultimodal LLMsTest-Time Compute ScalingModel MergingInterpretability & Emerging ResearchSystem Design: Emerging ArchitecturesSystem Design: Model MergingSystem Design: Test-Time Compute
A few sample questions
Just examples to set expectations - the real interview has many more and adapts to your responses.
“Can you explain what a Mixture of Experts model is and how it differs from a dense Transformer at a high level?
“Compare early fusion versus late fusion in multimodal model design. In which situations would you prefer one over the other?
“What is model merging, and why would someone want to merge two separately fine-tuned models rather than just training one model on combined data?