Reddit

Typical interview loop

How Reddit usually runs it for applied AI and LLM engineer roles.

1. 1

   Recruiter screen

   Focus: Fit & baseline ML fluency

   A short call on your background, the role and the loop, which sometimes includes a few basic ML questions.

2. 2

   Technical screen (hands-on ML notebook)

   Focus: Practical modeling & data handling

   A timed, notebook-style exercise where you inspect a provided dataset, clean it and get a reasonable model working while explaining your choices.

3. 3

   Onsite: ML fundamentals

   Focus: Conceptual ML depth

   An open-ended conversation on core ML and deep learning concepts that probes how deep your understanding goes.

4. 4

   Onsite: ML system design

   Focus: End-to-end ML design & infra

   Design an end-to-end ML system for a product problem, with follow-ups that push into infrastructure such as feature pipelines, serving latency and online A/B testing.

5. 5

   Onsite: coding

   Focus: Algorithms & clean code

   A standard data-structures-and-algorithms round of roughly medium difficulty where clean, working code and clear communication matter.

6. 6

   Onsite: hiring manager

   Focus: Ownership, collaboration & values

   A behavioral conversation about past projects, ownership and collaboration, plus how you fit the team and Reddit's values.

How it weights your plan

Selecting Reddit when you build a plan multiplies each topic’s priority score: