AI Trainer

Job Description

We are looking for a highly skilled and experienced AI Trainer to join our team. The ideal candidate will have a proven track record in training AI / ML models, designing datasets, and enhancing model accuracy. This role requires strong expertise in AI training methodologies, annotation techniques, and the ability to deliver consistent results across multiple domains.

Job Title : AI Trainer

Location : Coimbatore

Experience : Minimum 5 Years

Employment Type : Full-Time / Part-Time

Key Responsibilities :

Design, curate, and preprocess datasets for AI / ML model training.

Train, evaluate, and fine-tune AI models to meet performance benchmarks.

Develop and implement annotation guidelines, label strategies, and quality control processes.

Work closely with data scientists and engineers to improve model accuracy and relevance.

Monitor model performance, identify gaps, and provide continuous feedback for improvement.

Ensure ethical AI practices, data privacy, and compliance with standards.

Mentor and guide junior trainers or team members in AI training processes.

Requirements :

Minimum 5 years of experience as an AI Trainer or in a related role (data label, AI / ML model training, NLP, CV, or speech recognition).

Demonstrated track record of successful AI model training projects.

Strong understanding of machine learning concepts, supervised / unsupervised learning, and annotation techniques.

Hands-on experience with AI tools, frameworks, or platforms (TensorFlow, PyTorch, Hugging Face, etc.).

Familiarity with large language models (LLMs), computer vision, or conversational AI systems.

Excellent communication, documentation, and collaboration skills.

Nice to Have :

Exposure to reinforcement learning, generative AI, or fine-tuning large pre-trained models.

Experience in building domain-specific datasets.

Certifications in AI / ML or data science.

Interested candidates send your resume to jobs@prognova.co

Requirements

• AI / ML model training and fine-tuning
• Dataset design, curation, and preprocessing
• Annotation and labeling techniques with quality control
• Strong understanding of supervised and unsupervised learning
• Proficiency in AI frameworks (TensorFlow, PyTorch, Hugging Face, etc.)
• Experience with large language models (LLMs), computer vision, or conversational AI
• Model performance monitoring and optimization
• Collaboration, mentoring, and communication skills
• Knowledge of ethical AI practices and data compliance
• Proven track record in AI training projects