Training and Quality Manager

2 weeks ago

gautam buddha nagar, India Innodata Inc. Full time

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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