Training and Quality Manager
2 days ago
The Training & Quality Manager – AI/LLM Practice will lead global training and quality initiatives for AI/LLM projects, ensuring operational excellence, consistency, and compliance. The role focuses on building scalable training frameworks, standardizing quality processes, and driving continuous improvement across global teams. You'll collaborate with cross-functional and client stakeholders to strengthen delivery performance and enhance overall project quality in alignment with AI/LLM goals. Key Responsibilities - Lead global training and quality programs for AI/LLM projects ensuring consistency, accuracy, and compliance. - Design and implement scalable training frameworks, assessments, and certification programs. - Monitor performance metrics, identify skill gaps, and drive targeted upskilling initiatives. - Establish and enforce quality standards and continuous improvement processes across teams. - Conduct audits, calibrations, and root cause analyses to maintain excellence in delivery. - Partner with operations and client teams to align training and quality strategies with business goals. - Drive change management, governance, and cross-functional collaboration across global sites. Requirements: - Bachelor's degree required (Computer Science, IT, Engineering, Linguistics, or related field preferred). - 5+ years of experience in training leadership and quality management within AI, LLM, tech operations, or a process-driven environment. - Strong understanding of AI/LLM concepts, model training processes, and data-driven decision-making. - Proven track record of leading cross-functional, multicultural teams in a fast-paced global setup. - Excellent English communication, presentation, and stakeholder management skills. - Analytical mindset with the ability to design and monitor performance dashboards and quality metrics. - Demonstrated problem-solving, innovation, and change management capabilities. Good to Have: - Knowledge of process improvement methodologies (Six Sigma, Lean, Kaizen). - Experience working with AI model evaluation, policy compliance, or linguistic quality frameworks. - Exposure to client-facing roles in AI or technology projects. - Strong people leadership and mentoring skills.
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