Policybazaar (PB Fintech)

Typical interview loop

How Policybazaar (PB Fintech) usually runs it for applied AI and LLM engineer roles.

1. 1

   Written test or online assessment

   Focus: Screening, fundamentals

   Early-career candidates, including campus hires, sit a written or online test before any interviews, and it filters hard.

2. 2

   Case study discussion

   Focus: Problem framing, approach

   You talk through how you would approach a business problem with data, step by step.

3. 3

   Technical rounds

   Focus: ML fundamentals, maths, coding

   Several rounds on ML basics, common algorithms, coding and the maths behind deep learning.

Topics to prepare for Policybazaar (PB Fintech)

The topics its loop weighs most, each with what interviewers check and what to study.

• Embeddings basics: word2vec, contrastive learning, what embeddings captureML fundamentals
• Self-attention from scratchTransformers
• The decoder-only transformer (GPT forward pass)Transformers
• Python for ML interviewsCoding
• Calling LLM APIs in Python: async, streaming, retriesCoding
• Retrieval for RAG: chunking, hybrid search, rerankingRAG
• Evals and error analysisEvals
• Decoding: greedy, beam, temperature, top-k/top-pInference

How it weights your plan

Selecting Policybazaar (PB Fintech) when you build a plan multiplies each topic’s priority score: