describe Logistic regression
Machine Learning Engineer Interview Questions
6,176 machine learning engineer interview questions shared by candidates
I was given an engineering interview roadmap that will be outlined below verbatim: Recruiter phone screen (30 mins)-This is a chance for your recruiter to learn about your background and interests, what you are passionate about, and the impact you want to make in your next move. Technical phone screen (60 mins) - You will meet with an Affirm Engineer to further assess your technical skills through a live pair-programming session. Onsite - Practical coding (60 mins) - Like the technical phone screen, the practical coding session is intended to give us an opportunity to assess your coding ability, and other themes such as readability and decomposition. You should not expect to be doing heavy algorithmic questions. Instead, the questions we will work on together will be cross-cutting across a backend focus while still evaluating your general technical skill. Platform-specific questions may be asked depending on the context of the role. Onsite - Systems design (60 mins) -We will work through various technical problems that can be solved in a myriad of ways by defining the architecture, modules, interfaces and data that comprise a system. As part of the exercise, you may be asked to whiteboard some simple code or pseudocode to help illustrate your design Onsite - Hiring manager (60 mins) - this interview with the hiring manager will explore your background and skills. This interview will also give you the opportunity to ask questions about the team, projects you would be working on, and learn more about Affirm. Additionally, expect questions around contributing to Affirm’s culture of inclusion, working effectively with a global team and for prospective managers, your ability to ensure all team members are seen and heard equitably. Lastly, be prepared to share your experience with mentoring or leading all or part of a recent project. Offer - Congratulations, you made it! Your recruiter will schedule time with you to discuss offer details and talk through next steps.
I was asked to build a text document classifier and was given significant leeway in how I chose to design it.
How would you build a recommendation system that would benefit the company?
Example Questions: Q: How would you visualize and present a particularly complex data set? Q: How would deal with a high dimensional data set? Q: What ML techniques are you familiar with and what are the tradeoffs between them?
They had a pen and paper coding question to go over code snippet of an NN and training loop in PyTorch and explain, calculate, and fill in blanks
SQL, machine learning basic concepts, behavioural
Why Rakuten ?
Why do you want to work at Xomnia?
Just a conversation about my experience.
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