KO | EN

GitLite

Minimalist Open Source Repository Search Engine

gitlite — search

#dsh #dsh-plugin #ai-agents #developer-tools #typescript #codex #cli #claude-code #mcp #rust #deepseek-harness #ai-agent

crack-the-mle-interview

★ 19 Open GitHub ↗

ML algorithms and Leetcode stuff, in Python

// repository documentation

Was this content helpful?

★ 0 (0 ratings)

# Crack the MLE Interview

Topics to be expected in a Machine Learning Engineer interview:
- Algorithm Coding (same for SWE)
- ML Algorithm Coding
- ML Case Study
- Scalable System Design
- Behavioral Questions

Other topics that may appear:
- Linear Algebra
- Probability and Statistics
- Calculus

## Algorithm Coding
- Leetcode (Medium, Hard)

## ML Algorithm Coding
- Gradient Descent
- Decision Tree Split

## ML Case Study
### ML Modeling Knowledge:
- Feature Engineering
- Recommendation System
- Ranking
- Classification
- Regression
- Experimentation
### ML System Knowledge:
- Scale and Latency
- ML Architecture
- Layered/Funnel Approach and Real-time Serving
- Training and Prediction Monitoring

## Scalable System Design
- CAP Theorem
- Caching
- Partitioning and Sharding
- Push vs Pull model
- Big Data
- HTTP, web socket, long polling, RPC, etc
- Race condition
- SQL vs NoSQL

## Behavoiral Questions:
- Past Experience
- Culture Fit
- Leadership and Ownership
- Conflict Handling

https://docs.google.com/spreadsheets/d/1cPgFltD3hvjumxeGNw85e-Kujswi1zUVsNRrvAesgUk/edit?usp=sharing

crack-the-mle-interview

Explore Similar Repositories

Was this content helpful?

Recent Feedback

Download README