Machine Learning Engineer Intern Interview Questions

8,225 machine learning engineer intern interview questions shared by candidates

1. Deploy an ML Model as a REST-API Of your choosing, please deploy a computer vision machine learning model as a rest- api. The API should be written in Python. The API should be able to accept an image/video and return the output as JSON. An example: You could deploy a face recognition model that takes an image and returns the co-ordinates of the bounding box(es) localizing the face(s). Requirements An API endpoint that accepts an image and returns a result as JSON. Package the API in a Docker image for deployment. Optional Unit tests A log of all POST requests with timestamps. Ideally, persisted in a database. The assignment should contain all the code required to run it locally. For example, be sure to include Dockerfiles. The code should also be accompanied by documentation. Also provide a brief summary of your approach and discuss potential improvements.
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Machine Learning Engineer

Interviewed at Clarius Mobile Health

4.1
Nov 2, 2021

1. Deploy an ML Model as a REST-API Of your choosing, please deploy a computer vision machine learning model as a rest- api. The API should be written in Python. The API should be able to accept an image/video and return the output as JSON. An example: You could deploy a face recognition model that takes an image and returns the co-ordinates of the bounding box(es) localizing the face(s). Requirements An API endpoint that accepts an image and returns a result as JSON. Package the API in a Docker image for deployment. Optional Unit tests A log of all POST requests with timestamps. Ideally, persisted in a database. The assignment should contain all the code required to run it locally. For example, be sure to include Dockerfiles. The code should also be accompanied by documentation. Also provide a brief summary of your approach and discuss potential improvements.

Preprocessing: how would you optimize preprocessing if you had 1 million records in the database, just a little about CI/CD ML/DL: Embeddings (statistical methods + NN), similarity, what is RAG, interpolate, and extrapolate. If you have data from 2 years ago, how would you predict this year? Evaluate 2 chatbots, 2 models.
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Machine Learning Engineer

Interviewed at Tower Research Capital

4.1
Jul 25, 2025

Preprocessing: how would you optimize preprocessing if you had 1 million records in the database, just a little about CI/CD ML/DL: Embeddings (statistical methods + NN), similarity, what is RAG, interpolate, and extrapolate. If you have data from 2 years ago, how would you predict this year? Evaluate 2 chatbots, 2 models.

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