Companies rely on machine learning engineers to help design and improve the systems that allow their software to improve on its own, rather than being specifically programmed. During the interview process, be prepared to be tested heavily on both computer science and data science knowledge with an emphasis on recognizing patterns and trends. A bachelor's degree in computer science or a related field will be required.
OA: One longest interval with sum limit the other is string parsing and hashmap. Probability technical: the classical Seattle raining problem, uniform sphere sampling from uniform distribution, expected number of times of two consecutive coin heads, logistic regression gradient descent from scratch coding behavioral: talking about previous projects, what if disagree with supervisor, asking for help or solve by oneself.....
I cant give interview questions but it's medium leet code level
What experience do you have that can make you succeed at LinkedIn?
How to generate a uniform06 number using a nonuniform distributed function?
The coding question was about random number generators.
Case-based questions. What would you do if your algorithm performs poorly for x.
Binary tree
Usual coding, and ML system design questions. Coding part was a bit more ML/data science related
Q: Talk about why you would want to use a specific model.
What do you know about modern NLP techniques?
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