Training And Quality Manager ( Technical / Tier1 or Tier2 institute )

Experience :- 7yrs
Salary :- 35lpa
Location :- noida
Key Responsibilities
Technical Training & Capability Development
• 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 through assessments, production performance, and quality metrics and create targeted upskilling plans.
• Develop practical exercises, technical assessments, simulations, and certification frameworks.
Quality Management
• 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 and identify root causes of recurring defects.
• Partner with Operations and Program Managers to implement corrective and preventive actions.
• Drive continuous improvement initiatives to improve accuracy, consistency, productivity, and turnaround time.
AI Data & Technical Operations
• Provide technical guidance for projects involving:
o Data annotation and labeling
o LLM evaluation
o RLHF / human feedback
o Prompt-response evaluation
o NLP and text classification
o Image/video/audio annotation
o Generative AI evaluation
o Data validation and enrichment
o Model benchmarking and red teaming
• Understand project guidelines, client specifications, annotation taxonomies, and evaluation rubrics and translate them into effective training and quality programs.
• Work with SMEs and technical teams to resolve complex quality and interpretation issues.
Stakeholder Management
• Work closely 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.
Continuous Improvement
• Identify opportunities to improve training effectiveness, operational quality, and process efficiency.
• Use data and analytics to measure training ROI and quality improvement.
• Drive automation and technology adoption in training and quality processes.
• Standardize best practices across projects and delivery teams.
Required Skills & Experience
• 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.
Preferred Qualifications
• Certifications in AI/ML, Quality Management, Six Sigma, instructional design or technical training are preferred.
• 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.
. Tier 1 institutes or tier 2 institutes

Work arrangement
No