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Ml Engineer Interview Questions
1,787 ml engineer interview questions shared by candidates
- 6 hard quiz - questions with 4-6 T/F options (not necessarily from your everyday ML algorithms). - 1 medium leetcode problem (from their list of most repeated questions) - 2 implementation questions. Mine were KNN and Kmeans. - One neural network hand-calculation (easy) Overall the assessment was thorough, but the time limit is unreasonably low! As someone with tons of coding and ML experience, I could say you had to be top 10% of Stanford graduates so that you can come close to getting all the questions right in 70 mins.
Explain me loss? Go over attention for someone who doesn’t know the technical details.
Is K nearest neighbor supervised or unsupervised. What is regularization? Would you increase or decrease the learning rate if loss is oscillating. A LC hard graph question.
What is SVM in machine learning?
tf-idf on a dataset that they provide, manually load csv and fix broken dataset.
The most important question I was asked was about my educational and professional experience. They wanted to know how my studies and previous work experience have prepared me for this role and how I can contribute my skills to the company.
1. What is the difference between rdd's and dataframes? 2. What algorithms did you use to build the Question-Answering model (NLP)? 3. Tell me about different ML algorithms you use at work.
Explain projects, why RAG was used in your project, how was agentic architecture was setup, why and how vector db are indexed, how will you find most recurring topic of customer grievance from set of tech support scripts, what is temperature in LLM and what does it exactly do to modify output personality of a LLM. Programming: find second highest element in a list
Would you be able to talk to teams in Australia while you are based out of the US? Can you tell us how you would solve this problem that my manager and I have been stuck with for a month?
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