A fast-moving culture promotes rapid development and experimentation, and you can propose and execute end-to-end projects with minimal red tape.
The rapid deployment of projects leads to a lack of overall engineering rigor and mentorship. Lots of ML knowledge can be half-baked, and results are not understood well.
4 rounds in total: * 1 round with HR (15-30 minutes) * 2 rounds of tech interview (each 1 hour with medium-hard LC, ML questions, system design) * 1 final round (behavioral questions, about 1 hour)
45 mins resume deep dive about my previous Applied Scientist intern role, and 10 mins for a LeetCode medium question. The scope is a match (supply chain), but they are looking for people with LLM skills.
1. Application & Recruiter Screen Format: 30–45 min phone or video call Focus: Your background, motivation for TikTok, "Always Day 1" culture fit, plus 1–2 high-level ML questions (e.g., supervised vs. unsupervised learning, evaluation metrics). 2
4 rounds in total: * 1 round with HR (15-30 minutes) * 2 rounds of tech interview (each 1 hour with medium-hard LC, ML questions, system design) * 1 final round (behavioral questions, about 1 hour)
45 mins resume deep dive about my previous Applied Scientist intern role, and 10 mins for a LeetCode medium question. The scope is a match (supply chain), but they are looking for people with LLM skills.
1. Application & Recruiter Screen Format: 30–45 min phone or video call Focus: Your background, motivation for TikTok, "Always Day 1" culture fit, plus 1–2 high-level ML questions (e.g., supervised vs. unsupervised learning, evaluation metrics). 2