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Interview questions by company and topic | SysRound

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11 questions

Showing 1–11

Machine learningHard
Majority-Vote Labels from Three Noisy Annotators, Then Beat the Baseline
Companies: OpenAI
Annotation & Label Quality · ML Coding
Last reported Oct 2026
Open workspace
Machine learningMedium
Filter Bad Human Annotations
Companies: OpenAI
Annotation & Label Quality · Fairness & Bias
Last reported Apr 2026
Open workspace
ML system designMedium
Mine Novel Images from Unlabeled Data
Companies: OpenAI
Annotation & Label Quality · ML System Design · Unsupervised Learning
Last reported Apr 2026
Open workspace

Machine learningHard

Improve Training With Noisy Annotators

Companies: OpenAI

Annotation & Label Quality · Model Evaluation

Last reported Apr 2026

Machine learningHard

Improve classifier with noisy multi-annotator labels

Companies: OpenAI

Annotation & Label Quality · Model Evaluation

Last reported Feb 2026

ML system designHard

Select high-quality math documents from crawls

Companies: OpenAI

Annotation & Label Quality · Data Ingestion & CDC · ML System Design

Last reported Dec 2025

Machine learningMedium

Clean OCR data and build an LLM dataset

Companies: Microsoft

Annotation & Label Quality · Data Cleaning & Wrangling

Machine learningHard

Design an end-to-end spam detection system

Companies: Amazon

Annotation & Label Quality · ML System Design

Machine learningMedium

Design photo and listing quality models

Companies: Airbnb

Annotation & Label Quality · Ranking Models

Machine learningMedium

Evaluate Noisy Data for LLM Post-Training

Companies: Mercor

Annotation & Label Quality · Fine-Tuning & Alignment Techniques

Machine learningMedium

How LLM training data is sourced, labeled and quality-checked at each training stage

Companies: NVIDIA

AI Product Management · Annotation & Label Quality