Zuhaib Khaki

Zuhaib Khaki

Trainings Leader & DeepTech Educator

Zuhaib Khaki is a Trainings Leader and DeepTech Educator specializing in learning-experience design, training operations, and scalable AI education systems. At Chinar Quantum AI, he leads the operations of Transformative Learning Labs, manages high-performance training teams, and designs technical learning programs across data science and AI.

With a strong background as an AI Engineer, he combines technical expertise with leadership in training systems, delivering impactful learning experiences, building structured educational pipelines, and establishing the methodologies that support technology-driven skill development.

Experience

Operations LeadPresent

Chinar Quantum AI - Transformative Learning Labs (TLL)

  • Oversees operations and leads specialized trainers across multiple programs.
  • Establishes systems and processes supporting high-performance learning ecosystems.
  • Designs technical methodologies to accelerate learning in emerging technologies.
  • Coordinates program execution, quality, and alignment with organizational strategy.

DeepTech EducatorPresent

Chinar Quantum AI

  • Delivers technical training across data science, AI, NLP, and applied machine learning.
  • Trained hundreds of learners from diverse academic and professional backgrounds.
  • Supports curriculum development and designs learning pathways for new programs.

AI Engineer

Chinar Quantum AI

  • Implemented conversational features using RAG to streamline medical appointment booking for an MVP.
  • Architected a two-stage retrieval pipeline for a travel recommendation engine.
  • Worked with LangChain, vector embeddings, PyMongo, TFRS, and recommendation system architectures.

Education

New Delhi, India

B.Sc. in Mathematics

University of Delhi

Projects

Medical Appointment RAG Assistant

Developed conversational workflows using RAG to reduce time and complexity in appointment scheduling.

Tour Package Recommendation Engine

Designed a two-tower retrieval model for personalized recommendation using embeddings and TFRS.

Queue Reduction Prototype - Delhi Design Innovation Bootcamp

Built an early-stage prototype for reducing congestion at CNG stations during a month-long innovation bootcamp.

Skills

Learning-Experience DesignTraining OperationsTeam LeadershipTechnical CommunicationApplied MathematicsMachine LearningNLPData SciencePythonLangChainVector EmbeddingsPyMongoRecommendation SystemsRAG ArchitecturesC++Databases