Meta·Machine Learning Engineer·Onsite - Coding / Algorithms·Senior

Senior

Jun 2026

Summary

Meta coding round for an MLE role. One question, but it had layers. The core was a grid traversal problem with a twist that took me a minute to fully internalize.

Questions Asked (1)

Given a grid with walls, a start, an end, and some cells marked as bombs, find the shortest path from start to end. Stepping on a bomb destroys all wall cells within a certain Manhattan radius, making them walkable for the rest of the search. Each bomb can only be triggered once.

Algorithms & Data StructuresTechnical Trade-offs

Author's notes

My first instinct was plain BFS and I started coding before fully thinking through the state space.

Create a free account to read the full note

AI HintsAI Generated

Suggested Approach

Model the problem as a shortest path search on a state space where the state includes the current position and the set of triggered bombs. Use Dijkstra's algorithm or BFS with a priority queue, updating the grid dynamically when a bomb is triggered. Discuss the complexity and potential optimizations, such as precomputing bomb effects or using A* with a heuristic.

Pro tip: Clarify with the interviewer whether triggering a bomb is mandatory when stepping on it, and whether multiple bombs can be triggered in one step. Also, consider if the bomb's effect is permanent or temporary, as this affects state representation.

1. Understand the problem and constraints

Ask clarifying questions about bomb triggering, grid size, and movement rules. Confirm whether bombs are optional to trigger and if their effects are permanent.

2. Define the state space

Represent each state as (position, set of triggered bombs). Since bombs are triggered at most once, the set can be a bitmask if the number of bombs is small.

3. Choose the search algorithm

Use Dijkstra's algorithm because edge weights are uniform (each move costs 1) but the state space is large. Alternatively, BFS can be used if all moves have equal cost, but Dijkstra handles the dynamic grid updates more naturally.

4. Implement the search with dynamic grid updates

When a bomb is triggered, update the grid to mark walls within the Manhattan radius as walkable. Ensure that the state includes which bombs have been triggered to avoid re-triggering.

5. Analyze complexity and optimize

Discuss time and space complexity: O(R*C*2^B) where B is the number of bombs. Suggest optimizations like precomputing bomb effects or using A* with a heuristic to reduce search space.

Key Points to Mention

State representation: position and bomb trigger status (bitmask if few bombs).
Use of Dijkstra's algorithm or BFS with priority queue for shortest path.
Dynamic grid updates: when a bomb is triggered, walls within Manhattan radius become walkable.
Handling of bomb triggering: each bomb can be triggered at most once, and triggering may be optional.
Complexity analysis: exponential in number of bombs, so discuss trade-offs and potential optimizations.
Edge cases: start or end on a bomb, unreachable end, bombs with overlapping effects.

AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.