Groww
Retail investing and stockbroking app; hiring ML engineers for GenAI work
Interview in a few hours? A quick sprint for Groww
AI in interviews
No public policy found. Assume no AI assistance in live rounds unless your recruiter says otherwise.
Typical interview loop
How Groww usually runs it for applied AI and LLM engineer roles.
- Focus: Background, role fit
Screening call
A short conversation about your background, the role and your goals; you can apply directly or through a referral.
- Focus: CS basics, coding
Online assessment
A timed remote test mixing multiple-choice CS fundamentals with one or more programming problems; campus versions add aptitude.
- Focus: Problem solving, complexity
DSA round
An hour of live easy-to-medium data-structure problems where you're expected to state your approach and complexity before coding.
- Focus: LLM knowledge, project depth
AI/ML project discussion + design problem
For an AI/LLM-track role, half the round probed the candidate's GenAI projects and LLM understanding, then switched to a design-style logic problem solved in pseudocode.
- Focus: Working code, design trade-offs
Machine coding / system design (experienced hires)
Experienced engineers report a 90-120 minute build of a working, modular program and a separate open-ended design discussion of a large system.
- Focus: Ownership, motivation
Hiring manager / HR
A closing conversation that checks project depth and ownership, why you're moving, and notice period and compensation.
How it weights your plan
Selecting Groww when you build a plan multiplies each topic’s priority score:
Official prep and resources
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