Process
First, there is a self-introduction, followed by coding problems and questions about the details of your project. Although it is a Machine Learning position, many questions are asked about deep learning. The code problems involve writing down the process of self-attention on a whiteboard from scratch.
Questions
Can you describe the concepts of FlashAttention?
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Interview Statistics
The following metrics were computed from 29 interview experiences for the ByteDance Machine Learning Engineer role.
Success Rate
17%
Pass Rate
ByteDance's interview process for their Machine Learning Engineer roles is very selective, failing most engineers who go through it.
Experience Rating
Positive52%
Neutral24%
Negative24%
Candidates reported having very good feelings for ByteDance's Machine Learning Engineer interview process.
ByteDance Work Experiences
4.0
Too much work overtime
Machine Learning Engineer • Current Employee
Hangzhou, Zhejiang, China
March 17, 2022
Pros: Good salary, extra traffic compensation.
Cons: Too much work and pressure.
2.0
Bytedance work experience
Machine Learning Engineer • Former Employee
Shanghai, Shanghai
December 28, 2025
Pros: Nice employee benefit, global work experience, and large-scale business scenario.
Cons: The management system is chaotic, with unclear OKRs that are frequently changed. There is high work pressure with severe overtime issues and a lot of office politics. There is little emphasis on employee growth.
3.0
Machine Learning Engineer
Machine Learning Engineer • Former Employee
San Jose, California, United States
September 29, 2025
Pros: Good base; weekly happy hour
Cons: Fast pace; night meeting; RSU vesting policy.
- 4.0Too much work overtimeMachine Learning Engineer • Current EmployeeHangzhou, Zhejiang, ChinaMarch 17, 2022Pros: Good salary, extra traffic compensation.Cons: Too much work and pressure.
- 2.0Bytedance work experienceMachine Learning Engineer • Former EmployeeShanghai, ShanghaiDecember 28, 2025Pros: Nice employee benefit, global work experience, and large-scale business scenario.Cons: The management system is chaotic, with unclear OKRs that are frequently changed. There is high work pressure with severe overtime issues and a lot of office politics. There is little emphasis on employee growth.
- 3.0Machine Learning EngineerMachine Learning Engineer • Former EmployeeSan Jose, California, United StatesSeptember 29, 2025Pros: Good base; weekly happy hourCons: Fast pace; night meeting; RSU vesting policy.
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