Scale AI·Software Engineer·Technical Phone Screen·Intermediate

IntermediatePrefer not to say

Jun 2026Remote

Summary

Scale AI SWE coding round, one problem the whole session. It was a task scheduling design question that looked like a simple priority queue thing until the dependency constraints kicked in. Decent problem, made me think harder than I expected.

Questions Asked (1)

Design and implement a TaskManager class with an AddTasks method and a ConsumeTask method. ConsumeTask should return the executable task with the earliest deadline, where a task is only executable if all its prerequisite tasks have already been consumed. If no executable task exists, return NO_TASK.

Algorithms & Data StructuresSystem DesignTechnical Trade-offs

Author's notes

My first instinct was just a min-heap on deadlines and I started coding that up before I actually read the prerequisite part carefully.

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AI HintsAI Generated

Suggested Approach

Start by clarifying requirements and constraints, then propose a design that maintains a dependency graph and a priority queue of executable tasks. Explain how AddTasks updates the graph and queue, and how ConsumeTask efficiently retrieves the earliest-deadline executable task while updating dependents.

Pro tip: Discuss how to handle dynamic task additions and potential cycles, and mention that you would use a min-heap with lazy deletion or a balanced tree for efficiency. Also, consider thread-safety if the system is concurrent.

1. Clarify Requirements

Ask about task properties (ID, deadline, prerequisites), expected operations, concurrency needs, and error handling (e.g., cycles, missing prerequisites).

2. Design Data Structures

Propose a directed graph (adjacency list) for dependencies, a min-heap for executable tasks keyed by deadline, and a map from task ID to task details and dependency counts.

3. Implement AddTasks

For each new task, add to the graph, update dependency counts, and if it has no prerequisites, push it onto the heap. Handle duplicate IDs and cycles.

4. Implement ConsumeTask

Pop the min-deadline task from the heap, mark it consumed, and for each dependent task, decrement its prerequisite count; if it reaches zero, push it onto the heap. Return NO_TASK if heap is empty.

5. Analyze Complexity and Trade-offs

Discuss time complexity: O(log n) for heap operations, O(E) for dependency updates. Mention alternative approaches (e.g., topological sort with priority) and their trade-offs.

Key Points to Mention

Use a min-heap (priority queue) to efficiently retrieve the earliest deadline task.
Maintain a dependency graph and track the number of unconsumed prerequisites for each task.
When a task is consumed, update its dependents and add newly executable tasks to the heap.
Handle edge cases: no executable tasks, cycles, duplicate task IDs, and tasks with missing prerequisites.
Consider thread-safety if the TaskManager is accessed concurrently (e.g., locks or concurrent data structures).
Discuss time and space complexity, and potential optimizations like lazy deletion or using a Fibonacci heap.

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