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.
Assume we will develop a face recognition app where the facial photograph of the person will be taken on a mobile device and matched to a closed set of face images in the database. Outline the overall process of face identification, listing the fundamental steps (3-5) from preprocessing to the matching algorithm, with a few lines of explanation for each step. ii)Specify the challenges in the mentioned face recognition scenario and how you can deal with them.
It was a traditional human resource call.
Walk me through the OA questions
2 leetcode easy questions, one pure coding and one debugging. 1 ML related coding debugging.
Python lamda functions python oops concepts Python static methods Supervised machine learning Bias variance tradeoff
2nd interview: Basic ML questions that can be found by simple Google search. 3rd interview: Candidates are asked how good they are at team environments and how likely they are to collaborate with their project partners.
What is Your Tech stack, then they ask few questions related to basics of python like write list comprehension code, asked few algorithms from machine learning
Machine learning(Basics, RF, LR etc) Python Programming
Why do you want to work here
ML concepts and ML domain, leetcode graph questions.
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