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Eternal (Zomato)

Food delivery and quick commerce; ML for delivery-time, recs and GenAI

Target this company

Interview in a few hours? A quick sprint for Eternal (Zomato)

AI in interviews

low confidence

No public policy found. Assume no AI assistance in live rounds unless your recruiter says otherwise.

Checked 20 Oct 2026Source

Typical interview loop

How Eternal (Zomato) usually runs it for applied AI and LLM engineer roles.

  1. Referral and recruiter call

    Focus: Profile fit

    Candidates report getting in mainly through employee referrals, then a quick HR call to schedule rounds that often finish within days.

  2. Online assessment

    Focus: DSA, CS/ML basics

    A timed test of DSA coding problems plus MCQs; data-science openings have used ML/DS multiple-choice questions.

  3. Technical round: coding, projects, ML basics

    Focus: Coding, ML/RAG fundamentals

    Coding problems plus a project discussion, with ML questions on things like retrieval pipelines, neural-net training and embeddings for candidates with ML on their CV.

  4. Technical round: design and ML problem framing

    Focus: System design, ML framing

    Open-ended design built around Zomato's product, for example framing a prediction problem from delivery data and choosing the right signals.

  5. Engineering manager / HR round

    Focus: Culture fit, ownership

    A relaxed conversation on your past work, how you think, and culture fit; offers are sometimes given the same day.

How it weights your plan

Selecting Eternal (Zomato) when you build a plan multiplies each topic’s priority score:

Coding+20%
System design+20%
RAG+20%
ML fundamentals+10%

Official prep and resources

Public candidate write-ups

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