Gemini, Vertex AI and TPUs; ML loops still lean hard on DSA coding
Interview in a few hours? A quick sprint for Google
AI in interviews
Live interviews are AI-free: Google's candidate guide says using AI to answer questions, or submitting work you didn't produce, gets you disqualified. The one exception is a 2026 pilot where some junior and mid-level US software candidates may use Gemini in a code-comprehension round.
Typical interview loop
How Google usually runs it for applied AI and LLM engineer roles.
- Focus: Background and role fit
Recruiter screen
A short call about your background, the role and how the loop will run.
- Focus: DSA coding
Technical phone screen
One live data-structures-and-algorithms problem in a shared doc, with a second screen only if the first was inconclusive.
- Focus: Algorithms, clean code, edge cases
Onsite coding rounds
Several 45-minute algorithm rounds, which guides call the most heavily weighted part of the loop.
- Focus: Applied ML and system design
ML domain / ML system design
A round on applied ML knowledge and designing an end-to-end ML solution, explained clearly to different audiences.
- Focus: Values, leadership, past design
Googleyness & Leadership
A behavioral round that, under 2026 changes, also includes a technical design discussion of your past work.
- Focus: Calibration and leveling
Hiring committee and team match
A committee that never met you reviews the packet and sets the level, then you and hiring managers opt into a team.
How it weights your plan
Selecting Google when you build a plan multiplies each topic’s priority score:
Official prep and resources
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