PurpleTalk AI Engineer Interview Questions, Process, and Tips

Q1. What is the architecture of Transformer-based Large Language Models (LLMs)?
Ans. 
Transformer-based LLMs use self-attention and feedforward networks for processing sequential data efficiently.
• Architecture consists of an encoder-decoder structure, though many LLMs use only the decoder.

• Self-attention mechanism allows the model to weigh the importance of different words in a sentence.

• Positional encoding is used to retain the order of words since transformers do not have a built-in sense of sequence.

• Exa...read more
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Q2. What is the architecture of computer vision?
Ans. 
Computer vision architecture involves processing images through layers to extract features and make predictions.
• Input Layer: Receives raw image data, e.g., RGB values from a photo.

• Convolutional Layers: Apply filters to detect features like edges or textures, e.g., using 3x3 kernels.

• Pooling Layers: Reduce dimensionality while retaining important features, e.g., max pooling.

• Fully Connected Layers: Combine features to mak...read more
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Explain the various approaches to the Rag system.

Experience with Torch parallelism.

Q1. What projects have you completed to date?
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Q2. What are flow pipelines?
Ans. 
Flow pipelines are structured sequences of data processing steps that automate workflows in AI and data engineering.
• They consist of stages where data is ingested, processed, and outputted.

• Example: A data pipeline might extract data from a database, transform it, and load it into a data warehouse (ETL process).

• Flow pipelines can be used for machine learning model training, where data flows from preprocessing to model ev...read more
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Q1. Multi-Model Agentic systems
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Q2. What frameworks are you familiar with?
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