Meta·Machine Learning Engineer·Onsite - System Design / Architecture
- Design a recommendation engine from scratch.
“Spent the first few minutes just trying to scope it down because 'recommendation engine' could mean a hundred different things.”
FAANG / Big Tech
Most of these Meta write-ups come from Software Engineers (1,194), then Data Scientists (489) and Product Managers (453). The most reported rounds are the technical phone screen (1,190), the product sense round (466), the system design round (255) and the behavioral / leadership round (205).
2377 interview notes · updated Jul 2026
“Spent the first few minutes just trying to scope it down because 'recommendation engine' could mean a hundred different things.”
“This was the part I underestimated.”
“The fix itself is small, like a one-liner, but I spent way too long second-guessing myself because I kept looking for something more complex.”
“I started with airport capacity which in hindsight was the wrong entry point.”
“Went with BFS pretty quickly, felt solid.”
“This is a classic Meta-style metrics question and I probably overthought it.”
“My instinct was to jump straight to segmentation but they wanted me to slow down first.”
“The problem sounds simple on the surface but the recharge timing tripped me up.”
“Picked a mistake that felt safe and ended up sounding like I was humble-bragging about a minor thing.”
“Seemed deceptively simple at first and I think I wasted the first few minutes going too shallow.”