Snapchat·Machine Learning Engineer·Technical Phone Screen·Senior

SeniorPrefer not to say

Jun 2026Remote

Summary

Snapchat ML Engineer interview with a coding round that leaned more algorithm-heavy than I expected. The main problem was a classic DP string decoding question but they kept pushing with follow-ups until it got pretty uncomfortable.

Questions Asked (1)

Given a string of digits representing an encoded message where each number maps to a letter (1 to 26), count the number of distinct ways to decode it. Then optimize your solution to run in linear time with constant extra space. Follow-ups included returning the count modulo 1,000,000,007 for very large inputs, and extending the solution to handle streaming input where digits arrive one at a time.

Algorithms & Data StructuresTechnical Trade-offsSystem Design

Author's notes

I got the basic DP solution out fast enough, two variables tracking the last two states, felt good.

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AI HintsAI Generated

Suggested Approach

Start by explaining the recursive structure: at each position, you can decode one digit (if 1-9) or two digits (if 10-26). Then derive the DP recurrence and optimize it to O(n) time and O(1) space by keeping only the last two counts. Finally, address the follow-ups: modulo arithmetic for large inputs and streaming by maintaining a sliding window of the last two digits and counts.

Pro tip: For the streaming follow-up, emphasize that you only need the previous digit and the count from two steps back, so you can process digits in O(1) space and O(1) time per digit. Also, mention that modulo operations should be applied at each step to prevent overflow, and that the streaming version naturally handles very large inputs without storing the entire string.

1. Clarify the problem and edge cases

Confirm that digits map 1-26 to A-Z, and that '0' cannot be decoded alone. Discuss edge cases like empty string, leading zeros, and strings with '0' in the middle.

2. Derive the recurrence relation

Define dp[i] as the number of ways to decode the first i characters. Then dp[i] = (dp[i-1] if s[i-1] != '0') + (dp[i-2] if 10 <= s[i-2:i] <= 26). Explain base cases dp[0]=1 and dp[1]=1 if s[0]!='0' else 0.

3. Optimize to O(1) space

Observe that dp[i] only depends on dp[i-1] and dp[i-2]. Replace the array with two variables (prev2, prev1) and update them iteratively. This reduces space from O(n) to O(1).

4. Handle modulo and large inputs

For very large inputs, apply modulo 1,000,000,007 at each addition to keep numbers manageable. Explain that this doesn't affect the correctness of the count modulo the prime.

5. Extend to streaming input

For streaming, process each digit as it arrives. Maintain the last digit and the counts from the previous two steps. Update the counts based on the current digit and the previous digit, then shift the window. This gives O(1) time per digit and O(1) space overall.

Key Points to Mention

Dynamic programming recurrence: dp[i] = dp[i-1] (if single digit valid) + dp[i-2] (if two-digit valid).
Space optimization: only need last two DP values, so use two variables instead of an array.
Modulo arithmetic: apply modulo 1e9+7 at each step to avoid overflow and meet the requirement.
Streaming: maintain a sliding window of the last two digits and their corresponding counts; update in O(1) per digit.
Edge cases: '0' cannot be decoded alone; two-digit numbers must be between 10 and 26.
Time complexity: O(n) for the string version, O(1) per digit for streaming; space O(1) in both optimized versions.

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