ML Engineer Interview Questions
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Scaled Self-Attention Implementation — Meta
Implement scaled self-attention for Transformers: compute attention outputs and per-query weights from Q, K, V with masking and numerical-stability. Try coding
Snapchat ML Coding: K-Means + MapReduce Implementation
Prepare for Snapchat ML coding: implement deterministic K-means (centroids & assignments) and adapt it to MapReduce with mapper/reducer scripts. Learn iteration & stop rules.
Snowflake ML System Design: Cloud Anomaly Detection
Cloud anomaly detection system design for Snowflake interviews. Learn architecture, scaling, low-latency inference, security, and response mechanisms.
Tesla ML Coding Interview: 2D Conv Layer Forward in NumPy
Implement a 2D convolution forward pass in NumPy for channel-first inputs. Learn shape math, padding/stride handling, tests, and optimization tips. Try it now.
Top-k Video Similarity Search - Google ML Coding Interview
Top-k videos by multiplicative path similarity on a weighted directed graph. Also covers adapting to sharded/remote adjacency with API constraints. Includes tips.
Uber ML System Design: Scalable AI Chatbot with History
Design a scalable, low-latency AI chatbot backend with persistent history and real-time inference. Read architecture trade-offs and interview-ready design tips.
Visa ML Coding Question: Linear Regression Implementation
Implement linear regression with gradient descent (MSE) for Visa ML interviews. Return params (incl. bias) and per-epoch loss history; see tips and expected outputs.
WalmartLabs LLM Fundamentals Interview (Randomness)
Learn randomness in LLM training and inference—data sampling, initialization, dropout, temperature/top-k—and ways to control it. Prepare for interviews.
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