Machine Learning Engineer Interview Experience - San Jose, California
Process
Interview 1:
Self-introduction -- bias-variance trade-off, how to avoid overfitting/underfitting -- coding.
Interview 2:
Talk about research: how to find the closest vector to a given vector in N given vectors? How to approximate this when N is very large? Implement it in Python.
Questions
Interview 1: Self-introduction, bias-variance trade-off, how to avoid overfitting/underfitting. Coding.
Interview 2: Talk about research. How to find the closest vector to a given vector in n given vectors? How to approximate this when n is very large? Implement it in Python.
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Interview Statistics
The following metrics were computed from 2 interview experiences for the ByteDance Machine Learning Engineer role in San Jose, California.
Success Rate
ByteDance's interview process for their Machine Learning Engineer roles in San Jose, California is fairly selective, failing a large portion of engineers who go through it.
Experience Rating
Candidates reported having very good feelings for ByteDance's Machine Learning Engineer interview process in San Jose, California.
ByteDance Work Experiences
- 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.
- 5.0Great Food, Good VibesMachine Learning Engineer • Current EmployeeSan Jose, California, United StatesJune 19, 2025Pros: - Great food service. - Great working environment.Cons: Potential political challenges in the US.
- 4.0Great place to learn things quicklyMachine Learning Engineer • Current EmployeeSan Jose, California, United StatesSeptember 28, 2024Pros: Higher salary than Meta and Google at the same level.Cons: Low work-life balance in many teams.
ByteDance Interview Questions
