Machine Learning / AI

How do you feel about front-end tasks if they come your way?

What to do with ML model weights if they are several gigabytes in size? How to store them in the context of Docker?

What is the difference between CMD and ENTRYPOINT in a Dockerfile? Which can be overridden when running a container?

For storing sessions in an AI service, you mentioned Redis. Are there more modern solutions that support AI-specific operations like summarization?

How to avoid breaking production when deploying a problematic version that will start but work with errors?

How do you feel about classic backend tasks (PostgreSQL, Django) besides AI/API tasks?

Write a Python function that takes an unsorted list of integers and returns the median.

How to deploy a service to a specific group of nodes in Kubernetes?

How would you implement a database AI assistant (ClickHouse) that can answer questions, generate, and execute SQL queries? What stack and components would you use?

FROM python:3.11 COPY ./app WORKDIR /app RUN pip install torch transformers fastapi uvicorn sentence-transformers CMD ["uvicorn", "main:app", "--host", "0.0.0.0"]

What are layers in a Dockerfile and why is this concept needed?

What does the CrashLoopBackOff status mean for a pod in Kubernetes? What could be the problem?

Is there a mechanism in Kubernetes to check the status of a pod before it is included in the load?