Machine Learning Engineer Interview Questions
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Coupang ML System Design: Scalable E-commerce Search
Design a scalable e-commerce search system (semantic & vector search) for Coupang. Learn low-latency retrieval, ranking, filtering, and scaling choices.
Databricks ML Interview: Neural Networks & Transformers
Prepare for the Databricks ML interview: review Transformer components, self-attention, and Word2Vec (Skip-gram/CBOW). Read sample follow-ups and prep tips.
Databricks: Real-Time Harmful Content Detection (ML)
Databricks ML design: build a real-time harmful content detection system. Study architecture, latency trade-offs, monitoring, retraining and interview follow-ups.
Debug and Extend GPT-style Transformer — OpenAI ML Engineer
Fix 4 intentional bugs in a PyTorch GPT-style transformer, add KV-cache and a token classifier, and reproduce reference training outputs. Learn verification steps.
DoorDash Coding Question: Closest BST Node to Target
Find the integer node in a BST closest to a float target. Includes iterative and recursive solutions, complexity, edge cases and interview tips. Practice now.
eBay ML System Design: Post-Checkout Recommendations
Design a low-latency post-checkout recommendation system for eBay: retrieval, ranking, features, training, and metrics. Prepare for ML interviews with examples.
Google Coding Question: Online Longest Subarray with Average
Track longest contiguous subarray with average S online. Use prefix-sum key = pref - S*i with a hashmap. Read precision tips and complexity notes.
Google Coding Question: Task Scheduling with Precedence
Minimal makespan for DAG tasks with durations and precedence constraints on unlimited or M CPUs. Includes algorithms, complexity notes, and follow-ups.
Google ML Coding: Hand-code Multi-Head Attention in NumPy
Implement multi-head attention in NumPy: scaled dot-product for batched Q,K,V. Do per-head projections, reshape, apply mask, and return attention weights.
Google ML System Design: Fuzzy Video Deduplication
Design a real-time fuzzy video deduplication system using embedding models and ANN search. Learn tradeoffs, scalability, and appeal workflows—prepare for interviews.
Implement k-Fold Cross-Validation From Scratch — Uber
Implement k-fold, stratified, and time-series CV from scratch for ML evaluation. Includes split contracts, reproducibility, and aggregate metric. Read on to prepare.
LinkedIn ML: Large-Scale Streaming Mean & Variance
Compute population mean and variance in one pass over massive float streams. Includes mergeable, numerically stable summaries for distributed ML systems — try it.
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