Technical Screen Interview Questions
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Cisco CS Foundation: System Monitoring & Troubleshooting
Prepare for Cisco system monitoring interviews: master Linux process tools (ps, top, pgrep), inspect ports with ss/netstat/lsof, and test troubleshooting steps.
Cisco Object-Oriented Design: Customizable Chessboard
Practice Cisco OOD: design a flexible chessboard with customizable initial placement, move validation, and game-state tracking. Read implementation tips and follow-ups.
Coupang Coding Interview: Connected Components (Graph)
Count connected components in an undirected graph with BFS/DFS or Union-Find. See approach, complexities, and interview tips for Coupang ML Engineer. Read now
Coupang Infra Interview: Kubernetes Storage Management
Prepare for Coupang infrastructure screens: deep dive into Kubernetes storage, PV/PVC lifecycle, storage classes, and setup steps. Read practice follow-ups.
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.
Coupang System Design: Large Video Upload (Backend)
Plan a scalable, fault-tolerant large video upload system with chunked, resumable uploads, object storage and processing. Review trade-offs and interview prep.
Databricks Code: Shortest Path in a Fibonacci Tree
Find the node sequence on the path between two labels in a preorder Fibonacci tree (0/1-based). Get an index-based O(k+L) method for Databricks.
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 OOD Question: Scalable Playlist System Design
Design a scalable song playlist system for Databricks interviews — learn data models, APIs, concurrency strategies, and performance trade-offs. Get actionable guidance.
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.
Databricks System Design: Multi-threaded Event Logger
Design a multi-threaded event logger: thread-safe, low-latency architecture for high-throughput backends. Covers async batching, durable outputs, and backpressure.
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.
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