TikTok Software Engineer candidates describe a HackerRank-style assessment, LeetCode-style coding rounds, resume deep dives, and team-dependent design, SQL or frontend questions. Most reports here ended without an offer.
$189K
Avg. Base Comp
$257K
Avg. Total Comp
2-4 rounds
Typical Rounds
Not reported
Process Length
Candidates interviewing for TikTok Software Engineer roles describe a coding-heavy process where your resume gets as much scrutiny as your algorithms. Two started with a HackerRank-style online assessment of roughly two hours that mixed conceptual multiple-choice questions with coding problems. Others went straight from a recruiter screen into live rounds.
Live coding is the most consistent theme. Reported problems include graph questions such as finding island shapes in a matrix, level order traversal, and a stack problem. One candidate was asked a hard dynamic programming problem, and another had to write an LFU cache from scratch. Interviewers asked about time complexity, edge cases and how candidates would test their solutions, so practice explaining your approach out loud.
Expect to defend what you have built. Candidates describe walkthroughs of past projects, questions about their most recent work, and behavioral prompts such as how they handled a complex problem. A manager-style conversation in one loop still included a medium matrix problem.
The rest depends on the team. System design prompts included a messaging service, with the interviewer asking for depth on one component. Other loops covered SQL query improvement, networking and API basics, OS and thread fundamentals, or JavaScript topics such as async behavior and a debounce hook. Most of the reports here ended without an offer, so prepare the coding bar first.
Synthesized from 29 candidate reports by our editorial team.
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Featured question at Tiktok
Select the 2nd highest salary in the engineering department
| Question | |
|---|---|
| Top Three Salaries | |
| Monthly Customer Report | |
| Merge Sorted Lists | |
| Raining in Seattle | |
| Retailer Data Warehouse | |
| Employee Salaries (ETL Error) | |
| P-value to a Layman | |
| Flatten N-Dimensional Array to 1D Array | |
| Google Maps Improvement | |
| Basic Regex | |
| String Mapping | |
| Production Model Monitoring | |
| Hurdles In Data Projects | |
| Transformer Encoder Layer | |
| Duplicate Rows | |
| Messenger Service Design | |
| Target Value Search | |
| Concurrent LLM Serving | |
| The Longest Journey | |
| Post Success | |
| 7 Day Streak | |
| Diagnosing Query Speed Degradation | |
| Deciding Between Solutions | |
| Safe Deployments | |
| Swipe Payment API | |
| Scalable Data Pipelines | |
| f(x,y) in Interval | |
| Relational Migration | |
| Why Do You Want to Work With Us |
Synthesized from candidate reports. Individual experiences may vary.
Candidates describe starting with a recruiter or HR conversation about their background and fit. Scheduling differed by loop: one candidate said the recruiter booked each next round only after the previous one was passed, and another waited a couple of weeks after an interview ended early because of a technical error.
Two candidates report a timed HackerRank assessment of about two hours. One described 2 conceptual multiple-choice questions plus 3 coding problems, and the other 2 multiple-choice plus 2 coding questions. Not every candidate's loop opened with an assessment.
Reports describe one or two coding-focused technical rounds, including 1-hour phone interviews. Questions included medium graph problems in 40 to 50 minutes, a hard DP problem with interviewer hints, and an LFU cache. Interviewers followed up on complexity, edge cases and test cases.
Candidates report detailed questions about projects, the most challenging work they had done, and past technical contributions. Behavioral questions such as weaknesses or how they would work at TikTok came up. One manager-style round that began as a resume and soft-skills discussion still included a medium matrix manipulation problem.
Some candidates saw system design, such as a fulfillment-style system or a messaging service, where the interviewer wanted depth on one component. Others reported SQL query improvement, networking and API basics, OS, thread and database fundamentals, or JavaScript and React topics. Prepare these according to the team and your background.
