Amazon·Machine Learning Engineer·Onsite - System Design / Architecture
- Design a distributed data-preprocessing pipeline for LLM training. The reference architecture is S3 as the source, feeding into Kafka, then a tokenizer stage, near-duplicate deduplication, a quality filter, and finally an output sink. For each stage, justify your technology choices, explain what breaks at scale (throughput bottlenecks, data skew, fault tolerance, exactly-once semantics, schema evolution), and walk through how you'd monitor and recover from failures.
“This one ran the full hour.”