About the Role

As Technical Training and Quality Manager - AI Data, you will lead the training design and quality assurance programs for teams working on AI data annotation, labeling, evaluation, or model training data pipelines. You will bridge the gap between technical requirements (ML/AI teams) and operational execution (annotator/reviewer workforce)

Key Responsibilities

Training & Enablement

Design, develop, and deliver technical training programs for annotators, reviewers, and QA staff on AI/ML data labeling tools, guidelines, and workflows
Create onboarding curricula, training manuals, job aids, and certification programs for new hires
Continuously update training content based on evolving project guidelines, tooling changes, and model requirements
Conduct train-the-trainer sessions to scale training delivery across shifts/sites/regions
Track training effectiveness through assessments, pilot tests, and performance data

Quality Management

Define and maintain quality standards, rubrics, and scoring guidelines for data annotation/labeling tasks
Design and implement QA frameworks (sampling plans, audits, calibration sessions, inter-annotator agreement checks)
Monitor quality metrics (accuracy, consistency, throughput) and drive root-cause analysis for defects/errors
Partner with data scientists/ML engineers to translate model feedback into actionable quality improvements
Lead calibration sessions to align annotators/reviewers on edge cases and ambiguous guidelines

Process & Documentation

Own and maintain guideline documents, SOPs, and knowledge bases for each project/task type
Identify gaps in guidelines and drive clarification with project/product stakeholders
Build feedback loops between quality findings and training content updates
Standardize quality and training processes across multiple projects/programs

Cross-functional Collaboration

Work closely with Project/Program Managers, ML Engineers, Linguists, and Operations teams
Represent training/quality needs in project kickoffs and guideline design discussions
Report on training completion, quality trends, and risk areas to leadership
Support workforce planning by advising on staffing/skill requirements based on task complexity

Required Qualifications

Bachelor's degree in a relevant field (Computer Science, Linguistics, Education, or related); equivalent experience considered
7+ years of experience in training, quality assurance, or operations management, ideally within AI/ML data annotation, BPO, or tech-enabled services
Certification in Lean Six Sigma Green Belt
Strong understanding of AI/ML data lifecycle (labeling, annotation, RLHF, evaluation, etc.)
Experience designing training curricula and QA frameworks for high-volume operations
Excellent communication, facilitation, and stakeholder management skills
Analytical mindset with experience using quality/performance data to drive decisions

DIVERSITY, EQUITY, INCLUSION & BELONGING

At Innodata, Diversity, Equity, Inclusion, and Belonging are at the heart of who we are. With over 35 years of expertise, we foster an inclusive workplace that celebrates the rich diversity of backgrounds, experiences, and perspectives our employees bring — diversity that fuels our innovation in AI and data engineering. We encourage individuals from all walks of life to apply, particularly those who may feel they don't meet every qualification or who hesitate due to their identity. Through inclusive learning initiatives, Employee Resource Groups, and flexible work arrangements, we create a sense of belonging for every team member, whether remote or onsite.

How to Apply

Apply directly through this posting, and our team will be in touch.

Technical Training and Quality Manager, AI Data