Mukund Hingne

Delivers LLM training and evaluation across multiple client and AI-platform projects, including RLHF response assessment, prompt generation, and multi-step reasoning task design. Applies AI safety, bias-mitigation, and annotation-quality standards tailored to each project's guidelines.

Evaluated AI integration opportunities across marketing, sales, finance, operations, and training. Recommended automation solutions and produced structured reports translating technical capabilities into practical business applications.

Delivered 100+ live AI sessions to approximately 800 students, professionals, and corporate participants. Taught prompting, AI tools, research, productivity, and workflow automation through practical projects and guided exercises.

Evaluated, refined, and generated high-quality responses for RLHF-based LLM training, improving accuracy, coherence, reasoning, and safety. Designed complex multi-step reasoning tasks and structured question-answer workflows across domains including STEM.

Led educational content planning and development across subjects; mentored teams for consistency, quality, and scale. Strengthened learner engagement through structured, learner-centric instructional design.

Trained and evaluated LLMs through response assessment, prompt generation, output refinement, and annotation quality control. Applied AI safety and bias-mitigation principles and project-specific standards across technical and general-knowledge tasks.

Hands-on client delivery focused on responsible use, measurable adoption, and lasting internal capability. Delivery in English and Hindi, with internal-champion development and human accountability built into every engagement.

Pursuing a Master of Arts in Political Science, expected completion in April 2026.

Completed a Master of Technology in Machine Design in July 2021.