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Learning Engineer Interview Questions
6,584 learning engineer interview questions shared by candidates
Using a dataset provided, train a machine learning model around forecasting
Introduction, then ask leet code, then another round asks another leet code and also a network design question, which I still don't know, let alone the answer. Next round, ask leet code again and behavioural questions about which one interviewer was a really bad person.
estimating probability distributions for certain properties of other distributions. like estimating distance between two variable of a sorted samples of uniform distribution.
L1 Round: The interview began with questions about my recent projects, followed by foundational machine learning topics like supervised vs. unsupervised learning, structured vs. unstructured data, data preprocessing, EDA, and data visualization techniques. I was asked about box plots, including Q1 vs. Q3 formulas and whiskers. They included 3–4 simple riddle questions and ended with an easy Python coding task to print a right-aligned triangle pattern: * ** *** L2 Round: This round focused on deeper discussions about recent projects, LLMs, and Generative AI use cases. One scenario-based question involved integrating AI into a healthcare website to flag incorrect prescriptions via UI warnings. Other questions covered APIs, securing localhost environments before deployment, writing and giving examples of test cases, and long-term career goals. Finally, they revisited salary expectations.
Explain various statistical concepts to a non technical person
how you solved a tough situation in your project when all got stuck?
What is latent space/bottleneck in autoencoders and what is its purpose?
What is the most important thing in machine learning?
The take home assignment was confidential, but as long as someone has a good grasp of opencv, numpy and other standard Python computing libraries, should be doable. The third stage was about systems thinking and the questions were built upon the take home assignment e.g. how to scale the algorithm. There were some role-specific questions, which in my case was about MLOps.
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