Technical Fundamentals Check Questions
Assessment/checklist for foundational technical knowledge essential for software engineering roles, including algorithms, data structures, time and space complexity, basic mathematics, cryptography basics, and core systems concepts. Used to evaluate a candidate's ability to reason about fundamental problems and apply foundational techniques.
HardTechnical
0 practiced
Design an in-memory data structure that supports insert(x) in O(log n), delete(x) in O(log n), and find-median() in O(1). Describe your implementation choices, how you handle duplicates, and memory overhead. Provide pseudo-code for operations and explain trade-offs.
MediumTechnical
0 practiced
Explain the difference between eigenvectors, singular value decomposition (SVD), and principal component analysis (PCA). Give intuition for each and describe a practical pipeline where you would use SVD to compute PCA for dimensionality reduction on a term-document matrix.
HardTechnical
0 practiced
You are running out of GPU memory during model training with a large batch size and deep network. Propose concrete strategies to reduce memory footprint such as mixed precision, gradient checkpointing, activation offloading, model parallelism, and gradient accumulation. For each technique explain implementation complexity and performance trade-offs.
HardSystem Design
0 practiced
Design a parameter-server-based architecture to support synchronous distributed training for a model with 10 billion parameters across 100 worker nodes. Describe parameter sharding, gradient aggregation, consistency semantics, network bottlenecks, checkpointing, and strategies to reduce network bandwidth such as quantization and sparsification.
MediumTechnical
0 practiced
Given a SQL table 'events(id PK, user_id, event_type, occurred_at TIMESTAMP)', write an efficient SQL query to return each user's most recent event. Explain which indexes you would add to support millions of events per day and trade-offs for writes vs reads.
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