Скачать или смотреть AI-Training Data Specialist: Role, Day-to-Day & Career Guide

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An AI-Training Data Specialist curates, labels, and validates datasets that power machine learning models, ensuring data quality, coverage, and alignment with product goals. In medium–large companies—often remote or hybrid—this role is critical to reduce bias, improve model performance, and deliver reliable AI features. This video condenses what you need to know: core responsibilities like dataset design, annotation guidelines, quality audits, and edge-case triage; the real tools and skills that get hires noticed (data review, labeling platforms, SQL, clear annotation instructions, and pragmatic judgment); and the collaboration points with ML engineers, product managers, and legal/compliance teams. Expect a mid-level role with frequent decision-making around trade-offs, tight deadlines for iteration, and stress when quality issues impact customer-facing models. Typical US salary ranges run roughly $70k–$120k depending on seniority and location; roles are often remote-friendly and offer strong growth into MLOps, data engineering, or product roles. Watch to get practical examples, hiring tips, and what to look for in resumes. Managers and hiring leaders: connect with me on LinkedIn to discuss hiring strategies or location-specific salary benchmarks.

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Interview Questions:    • 🎙️ Job Interview Questions Answered  
Improvement at Work:    • 📈 Improvement at Work  


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