Instacart·Software Engineer·Technical Phone Screen·Intermediate

IntermediatePrefer not to say

Jun 2026Remote

Summary

Instacart backend coding screen, pretty focused on interval math and salary computation. Nothing crazy but the follow-up on complexity tripped me up a bit.

Questions Asked (1)

You have a list of workers, each with an hourly rate and a set of work intervals. Given a worker ID and a time range, compute the total salary earned within that range by summing the pay for each interval's overlap with the query window.

Algorithms & Data StructuresSystem DesignTechnical Trade-offs

Author's notes

I got the core logic down pretty quickly, just clamp each interval to the query bounds and accumulate.

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AI HintsAI Generated

Suggested Approach

Clarify the problem constraints and data structures first, then outline an algorithm that iterates through the worker's intervals, computes the overlap with the query range, and sums the pay. Discuss trade-offs between different approaches (e.g., linear scan vs. preprocessed sorted intervals with binary search) and consider edge cases like no overlap or invalid inputs.

Pro tip: Mention that you would preprocess intervals by sorting and merging them to handle overlapping intervals and enable efficient queries, especially if multiple queries are expected. This shows foresight and scalability thinking.

1. Clarify requirements and constraints

Ask about input format, data size, query frequency, and whether intervals can overlap. Confirm the definition of 'overlap' and how to handle partial hours.

2. Design the algorithm

Propose a method to compute the overlap between each work interval and the query range, multiply by the hourly rate, and sum. Consider if intervals are sorted or if preprocessing is needed.

3. Analyze complexity and trade-offs

Discuss time and space complexity of the chosen approach. Compare linear scan (O(n) per query) vs. preprocessing with binary search (O(log n) per query after O(n log n) preprocessing).

4. Handle edge cases and optimizations

Address cases like no overlap, zero-length intervals, negative rates, and multiple queries. Suggest optimizations like merging overlapping intervals or using a segment tree.

5. Test and validate

Walk through a simple example to verify correctness. Mention unit testing and potential pitfalls like off-by-one errors in overlap calculation.

Key Points to Mention

Overlap calculation: max(0, min(end1, end2) - max(start1, start2))
Time complexity: O(n) per query for linear scan, O(log n) per query with preprocessing
Preprocessing: sort intervals by start time and merge overlapping intervals
Edge cases: no overlap, query range outside all intervals, zero-duration intervals
Scalability: handling multiple queries efficiently with binary search or interval trees
Data types: using appropriate numeric types for rates and durations to avoid precision issues

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