Digital ops Professionals

Job Title: AI/ML Data Annotation Trainer

Location: Bangalore

Job Type: Full-Time

About the Role: We are looking for an experienced AI/ML Data Annotation Trainer who is well-versed in Computer Vision, Large Language Models (LLMs), and other relevant domains. The ideal candidate will have a strong understanding of AI/ML workflows, data annotation techniques, and quality assessment methods. This role involves training teams on best practices for data labeling, annotation tools, and model performance optimization.

Key Responsibilities:

• Design and deliver training sessions on AI/ML Data Annotation processes, including Image, Video, Text, and Audio annotation.


• Develop and maintain training materials, SOPs, and guidelines for various annotation projects.


• Provide hands-on training on annotation tools and platforms such as CVAT, Labelbox, SuperAnnotate, or similar.


• Educate teams on quality control mechanisms, best practices, and techniques for improving annotation accuracy.


• Train teams on data pre-processing, bias mitigation, and annotation standards for Computer Vision, NLP, and Multimodal AI models.


• Conduct assessments and evaluations to measure trainees performance and improve training methodologies.


• Collaborate with project managers, quality analysts, and other stakeholders to align training with business needs.


• Stay updated with the latest advancements in AI/ML and data annotation practices to refine training content.

Required Qualifications & Skills:

• Bachelors or Master s degree in Computer Science, AI/ML, Data Science, or a related field.


• 3+ years of experience in AI/ML data annotation, data labeling, or AI model training.


• Strong knowledge of Computer Vision, NLP, Large Language Models, and AI/ML model training workflows.


• Experience with annotation tools such as Labelbox, CVAT, Supervisely, V7 Labs, or similar.


• Familiarity with Python, TensorFlow, PyTorch, or OpenCV is a plus.


• Excellent training, mentoring, and communication skills.


• Ability to analyze and troubleshoot data annotation quality issues.


• Experience in working with cross-functional teams in an AI/ML environment.

Preferred Qualifications:

• Experience in training teams for large-scale AI/ML projects.


• Understanding of model evaluation metrics and data augmentation techniques.


• Previous experience working in data annotation for autonomous vehicles, healthcare AI, or retail AI.


• Certification in AI/ML or related fields is an advantage.