Technical Training & Quality Manager

Emploi pas sur LinkedIn

🕒 il y a 17 jours

🇺🇸 États-Unis – Télétravail

💵 $145 000 - $175 000 / an

⏰ Temps Plein

🟠 Senior

🔴 Expert

👔 Manager

👻 Score fantôme 20%

Ce que ça veut dire : la probabilité que cette offre reste ouverte sans recrutement actif.Comment le lire : 60 % ou plus, on pense que c'est une offre fantôme. Un score plus bas est moins inquiétant.Comment on la calcule : ancienneté, republications, postes ouverts vs taille de l'équipe, rapidité de clôture, et si le salaire est indiqué.À noter : une estimation à partir de données publiques, pas un jugement sur l'entreprise. De vraies offres peuvent avoir un score élevé, alors prenez-le comme un indice, pas comme un fait.

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InnoData

Site WebLinkedInTous les Emplois

2 - 10 employés

Fondée en 2019

🤝 B2B

💼 Conseil

🌍 Impact social

B2B • Consulting • Social Impact

InnoData est INNOvation DATA SCS, une coopérative sociale italienne basée à Foggia, spécialisée dans la fourniture de solutions technologiques. Le site web de l'entreprise (actuellement en maintenance) met en avant les "Soluzioni tecnologiche" (solutions technologiques) et l'impact social ("Impatto sociale"). Les coordonnées incluent Via Francesco Crispi 65, 71121 Foggia, Italie. D'après les informations disponibles, InnoData semble opérer à l'intersection de la technologie et de l'impact social, en proposant probablement des services axés sur la technologie à d'autres organisations.

Description

• Design and execute technical training programs for AI data and annotation teams • Develop training curricula, learning paths, assessments, certification programs, and refresher modules • Train teams on AI/ML concepts, LLMs, Generative AI, NLP, data annotation, data labeling, model evaluation, prompt engineering, RLHF, and AI response quality • Conduct Train-the-Trainer programs and build internal technical trainers • Identify skill gaps and create targeted upskilling plans • Develop practical exercises, technical assessments, simulations, and certification frameworks • Own quality frameworks and standards across AI data projects • Define and monitor quality KPIs, accuracy, agreement rates, defect rates, audit scores, rework, and productivity • Establish quality calibration processes and conduct regular quality audits • Analyze quality trends, identify root causes, and implement corrective and preventive actions • Drive continuous improvement to improve accuracy, consistency, productivity, and turnaround time • Provide technical guidance for data annotation, LLM evaluation, RLHF, prompt-response evaluation, NLP, multimedia annotation, Generative AI evaluation, data validation, model benchmarking, and red teaming projects • Translate project guidelines, client specifications, annotation taxonomies, and evaluation rubrics into training and quality programs • Work with SMEs and technical teams to resolve complex quality and interpretation issues • Collaborate with clients, Program Managers, Operations, Engineering, Data Science, and QA teams • Participate in client calibration sessions and quality reviews • Present quality dashboards, training effectiveness, RCA findings, and improvement plans to senior leadership • Support new project launches through training needs analysis, SOP development, quality framework creation, and readiness assessments • Measure training ROI and quality improvement using data and analytics • Drive automation and technology adoption in training and quality processes • Standardize best practices across projects and delivery teams

🎯 Exigences

• 8–12 years of experience in AI/ML, data operations, data annotation, AI training, quality management, technical L&D, or related areas • Bachelor's/Master's degree in Computer Science, Engineering, Data Science, AI/ML, Statistics, or a related field • Strong understanding of Artificial Intelligence, Machine Learning, Generative AI and LLMs • Experience working with AI data / annotation / model evaluation projects • Experience managing training and quality teams in a high-volume delivery environment • Strong analytical and problem-solving skills • Experience with Root Cause Analysis, CAPA, calibration, quality audits and process improvement • Strong stakeholder and client management skills • Excellent communication, presentation, and facilitation skills • Ability to convert complex technical concepts into easy-to-understand training content • Experience with AI platforms, annotation tools, LLM evaluation frameworks, or data-quality platforms • Exposure to Python, SQL, analytics/BI tools, or automation would be an advantage