Training And Quality Manager - AI Data Programs

Innodata Inc.; India; On-site; INR 2,000,000 - 3,200,000; Full time

Job summary

Innodata Inc. in India seeks a Technical Training & Quality Manager – AI Data to lead training programs, capability development, and quality assurance for AI data workflows across annotation, labeling, model evaluation and RLHF.

You will collaborate with AI/ML, Data Science, Operations, and Program Management teams to ensure teams meet client-defined quality standards and continuously improve processes in high-volume, fast-paced data operations.

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/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.

Responsibilities

• 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.
• 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.
• Provide technical guidance for projects involving: Data annotation and labeling, LLM evaluation, NLP and text classification, Generative AI evaluation, Data validation and enrichment, 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.

Skills

AI/ML concepts

Training management

Quality management

Data operations

Root cause analysis

Stakeholder management

Presentation skills

Education

Bachelor's/Master's in CS/Engineering/Data Science

Tools

Python

SQL

Analytics tools

Job description

We are looking for a Technical Training & Quality Manager – AI Data to lead technical training, capability development, quality assurance, and continuous improvement for AI data programs.

The role will work closely with AI/ML, Data Science, Operations, Program Management, and Quality teams to ensure that teams working on data annotation, data preparation, model evaluation, RLHF, LLM training, AI response evaluation, and other AI-data workflows have the required technical capabilities and consistently meet client-defined quality standards.

The ideal candidate should combine strong technical understanding of AI/ML and data workflows with hands‑on experience in training, quality management, process improvement, and large‑scale operations.

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:
• Data annotation and labeling
• LLM evaluation
• NLP and text classification
• Generative AI evaluation
• Data validation and enrichment
• 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.

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.