AI Data Training & Quality Lead

Innodata Inc.; United States; À distance; USD 145 000 - 175 000; Plein temps

Résumé du poste

Innodata Inc. is seeking a Technical Training & Quality Manager – AI Data to lead training, capability development, and quality assurance for AI data programs.

You will collaborate with AI/ML, Data Science, Operations, and QA teams to ensure teams maintain high-quality data workflows and meet client standards. The role requires strong AI/ML technical understanding, hands-on experience in training, QA, and process improvement, and the ability to scale operations across large datasets and multiple

Qualifications

• 8–12 years of experience in AI/ML, data operations, data annotation, AI training, quality management, technical L&D, or related areas.
• Bachelor's or Master's degree in a related field such as CS, Engineering, Data Science, AI/ML, Statistics.
• Strong understanding of AI, ML, Generative AI and LLMs.

Responsabilités

• Design and execute technical training programs for AI data and annotation teams.
• Develop curricula, assessments, certifications, and refresher modules.
• Train teams on AI/ML concepts, LLMs, NLP, data annotation, model evaluation, prompt engineering, RLHF, and AI response quality.
• Establish quality KPIs, audits, and continuous improvement plans.

Connaissances

AI/ML knowledge

Training program design

Quality management

Stakeholder management

Communication & facilitation

Process improvement

SOP development

Formation

Bachelor's/Master's in CS/Engineering/Data Science/AI/ML/Statistics

Outils

Python

SQL

Analytics/BI tools

AI platforms

Annotation tools

Description du poste

Innodata Inc. is seeking a Technical Training & Quality Manager – AI Data to lead training, capability development, and quality assurance for AI data programs.

You will collaborate with AI/ML, Data Science, Operations, and QA teams to ensure teams maintain high-quality data workflows and meet client standards. The role requires strong AI/ML technical understanding, hands-on experience in training, QA, and process improvement, and the ability to scale operations across large datasets and multiple