Process
I took the interview last summer.
The questions were easy, and the interviewers and recruiters were nice.
The process took longer than usual; it took me more than a month to get a verbal offer.
I declined after that.
Questions
Phone:
Decode string, e.g., input “3[a2[c]]”, output “accaccacc”.
What if the string is a stream that cannot fit into memory?
Onsite:
- LRU Cache
- Implement KNN
- Bias-variance tradeoff
- Why curse of dimensionality
- Discussion of convergence of SGD (or GD)
- Why cross-validation
Min height tree
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Interview Statistics
The following metrics were computed from 36 interview experiences for the Apple Machine Learning Engineer role in United States.
Success Rate
Apple's interview process for their Machine Learning Engineer roles in the United States is extremely selective, failing the vast majority of engineers.
Experience Rating
Candidates reported having very good feelings for Apple's Machine Learning Engineer interview process in United States.
Apple Work Experiences
- 5.0Growth Despite Top-down DirectionMachine Learning Engineer • Current EmployeeSingapore, SingaporeOctober 6, 2025Pros: Good perks. Lots of room to grow.Cons: Too much top-down direction from leadership.
- 4.0Good Culture, Workload StressMachine Learning Engineer • Current EmployeeNovember 5, 2022Pros: Nice benefits, good culture, good workplace environment.Cons: Work-life balance / workload balance. No free food.
- 3.0Good pay. Not great workMachine Learning Engineer • Current EmployeeCupertino, California, United StatesDecember 11, 2021Pros: - Stellar pay after stock appreciation. - Good benefits.Cons: - Not all teams have interesting problems to solve. Work gets boring sometimes. - Talent quality is not consistent. This would obviously vary team by team. From where I stand, half of co-workers are seriously subpar (bad engineering/problem solving, move very slowly).
Apple Interview Questions
