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ByteDance interview notes, page 9 of 29

FAANG / Big Tech

Most of these ByteDance write-ups come from Software Engineers (194), then Machine Learning Engineers (45) and Data Scientists (17). The most reported rounds are the technical phone screen (227), the system design round (28), the behavioral / leadership round (16) and the onsite coding round (9).

289 interview notes · updated Sep 2026

ByteDance·Software Engineer·Technical Phone Screen

May 2026
Bytedance SWE interview that threw a classic LC problem at me and then immediately asked me to extend it in a way I hadn't prepped for. The follow-up was the real test.
  • Given a string containing '(', ')', and '*' where '*' can represent '(', ')', or an empty string, determine whether the string can be made into a valid parenthesis sequence.
  • Follow-up: using DFS or backtracking, enumerate ALL distinct valid strings you can produce by replacing each '*' with '(', ')', or an empty string. Write your own test cases and verify them.

“I knew this one.”

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ByteDance·Software Engineer·Technical Phone Screen

May 2026
Bytedance SWE coding round, one question the whole time but it had way more surface area than it looked. The validation requirements are what got me, not the arithmetic.
  • Implement a calculator that evaluates an expression string containing only non-negative integers with + and - operators. The input must be validated and rejected if it's empty, has consecutive operators, has leading or trailing operators, contains non-digit characters, or has numbers with leading zeros (except the literal '0'). Discuss edge cases and complexity.

“I jumped straight to the parsing logic and had a working solution pretty fast, then they started poking at edge cases and I slowly realized I'd ignored half the prompt.”

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ByteDance·Machine Learning Engineer·Technical Phone Screen

May 2026
Bytedance MLE interview that went deep on tree-based models and regularization theory. The main question was a multi-part explainer on XGBoost vs a single decision tree, with follow-ups that got progressively more math-heavy. Felt more like a seminar than a standard interview.
  • Why does XGBoost tend to overfit less than a single decision tree? Walk through the specific mechanisms that control complexity and improve generalization, and then describe the conditions where XGBoost can still overfit and how you'd catch and fix it.
  • Write out the regularized XGBoost objective and derive the optimal leaf weight and the split gain formula from a second-order Taylor expansion. Where exactly do lambda and gamma appear?
  • If your XGBoost model is overfitting, which hyperparameters would you adjust first and in what direction? What trade-off does each one make?
  • Compare how Random Forest and XGBoost each resist overfitting relative to a single tree. When would you actually prefer Random Forest?

“This is a big question and I underestimated how far they wanted me to go.”

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ByteDance·Frontend Engineer·Technical Phone Screen

May 2026
Bytedance frontend interview that went heavier on algorithms than I expected. They gave me a classic array problem but the follow-up on time complexity tradeoffs is where things got interesting.
  • Given an integer array and a number k, find the kth largest element in the array.

“I jumped straight to sorting and they let me finish, then asked if I could do better.”

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ByteDance·Software Engineer·Onsite - Behavioral / Leadership

May 2026
Behavioral round at Bytedance for a software engineer role. One meaty question about problem-solving that took up most of the time. Felt like they really wanted to see how you think, not just what you built.
  • Walk me through a complex technical or organizational problem you solved. What made it hard, how did you approach it, what trade-offs did you consider, who did you involve, and what would you change looking back?

“This question is deceptively wide and I kind of rambled for the first minute trying to pick the right story.”

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ByteDance·Software Engineer·Technical Phone Screen

May 2026
Bytedance SWE interview threw a variant of the classic string addition problem at me, basically the same as LeetCode 415 but with raw character arrays instead of strings. Pretty standard algorithmic round, nothing too wild.
  • Given two non-negative integers represented as character arrays of digits (most significant digit first), return their sum as a character array. You cannot convert to a built-in big integer type or use any arbitrary-precision library.

“I recognized it as an add-strings variant pretty fast, which was both good and slightly dangerous because I jumped into code before fully thinking through the carry-on-final-digit edge case.”

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ByteDance·Software Engineer·Technical Phone Screen

May 2026
Bytedance SWE interview with a graph traversal problem that sounds deceptively clean on paper but has enough edge cases to trip you up if you're not careful.
  • You're given a list of currency exchange rate pairs and a set of queries. For each query asking for the rate from currency A to currency B, return the result by traversing a graph of known rates. Return -1.0 if either currency is unknown or no path exists between them.

“My first instinct was to just build an adjacency map and do DFS, which worked, but I fumbled the edge case where one of the currencies in the query doesn't exist in the graph at all.”

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ByteDance·Machine Learning Engineer·Technical Phone Screen

May 2026
Bytedance ML engineer screen, one coding question the whole time. Pretty standard dynamic programming territory but the linear time constraint is what makes it interesting. Left feeling okay about it.
  • Given an integer array that can contain positive numbers, negative numbers, and zeros, find the maximum product you can get from any non-empty contiguous subarray. Solve it in linear time.

“The basic idea clicked fast but I kept second-guessing myself on the negative number case.”

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ByteDance·Machine Learning Engineer·Technical Phone Screen

May 2026
Bytedance ML Engineer interview that went deep on RL theory and attention mechanisms. The breadth was manageable but the follow-ups got pretty surgical, especially on TRPO. Not a lot of fluff here.
  • What is the difference between on-policy and off-policy reinforcement learning, and how does importance sampling come into play?
  • Walk me through TRPO: the trust region constraint, how the natural gradient step works, and why the method provides monotonic improvement guarantees.
  • How does PPO approximate TRPO's trust region, and what does the clipped surrogate objective actually do?
  • Explain Generalized Advantage Estimation and the role of lambda and gamma in the bias-variance tradeoff.
  • How does linear attention reduce the complexity of standard attention, and what do you lose compared to softmax attention?
  • What is group-query attention, how does it differ from multi-head and multi-query attention, and what tradeoffs does it introduce?

“I knew the definitions cold but fumbled a bit explaining why importance sampling is necessary for off-policy methods.”

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ByteDance·Software Engineer·Technical Phone Screen

May 2026
SQL round for a Data Engineer role at Bytedance. One meaty question, about 30 minutes, felt like they wanted to see if you actually think in sequences and not just joins.
  • Given a users table and a logs table containing login attempt records, write a query to find users who had at least 3 consecutive failed login attempts on a specific date. Return the user's email, the count of consecutive failures, and the timestamps of the first and last failure in that streak.

“This tripped me up more than I expected.”

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