To listen to the phrase and repeate it.
Ml Engineer Interview Questions
2,740 ml engineer interview questions shared by candidates
tell me about your last job
The initial technical interview was a take-home assessment which I remember being something like the following: You are tasked with building a development environment on Google Cloud Platform (GCP) for a new web application. This environment needs to include: - A virtual machine (VM) instance. - A PostgreSQL database instance for the application's data storage. - Secure access to the VM instance via SSH. Requirements: - Use Terraform to define and provision the infrastructure. - The Postgres database instance should be accessible by the VM instance but not directly exposed to the public internet. Utilize Google Cloud's security best practices. Bonus points: - Can you configure the Terraform code to use environment variables for sensitive information like the GCP project ID or zone? - Can you modify the code to allow SSH access only from specific IP addresses for enhanced security?
They asked about different gcp services, then explanations about how a model is built and deployed on gcp. Model monitoring on gcp Projects from gcp and how everything was containerised
What do you know about ML
Explain vector embeddings and about how a LLM works
nothing, i don't want to provide here
Logistic regression, max pooling, K-Means clustering, etc
basic ML and deep learning questions
The questions covered topics like the difference between logistic regression and linear regression, random forest, K-means clustering, and max pooling. Additionally, I was asked project-based questions, including which algorithms were used in my project.
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