First round Python, and pandas scenario based joining dataframes , explode and crosstab fxn to be used for achieving desired output. Next Related to pyspark where they give you scenario and one was related to api creation using python flask. Sql scenario Airflow and kubeflow knowledge check
Talk a about you previous work experience?
Tell me about your experience and projects.
Asked about Machine learning/Deep Learning - NLP-based questions like pre-processing techniques for NLP, overfitting, backpropagation, transformers, vanishing gradient, exploding gradient, LLM, RNN, activation functions, bias, and variance, about the Python Language. They also asked questions about your projects and past internships/jobs.
What are you working on currently in terms, why this role etc
Precision vs recall Data structure concepts
To listen to the phrase and repeate it.
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
Viewing 911 - 920 interview questions