Hiren Ghughal

Trained and evaluated LLM outputs using RLHF workflows across 8+ rubrics (e.g., quality, factual correctness, compliance) to improve response accuracy and alignment. Applied prompt engineering and adversarial testing to identify failure modes and raise dataset quality for iterative reward training.

Shifted a timeshare model to a subscription membership platform by running customer discovery interviews and defining business requirements, including loyalty modules to improve engagement and unit economics. Scoped and architected an AI chatbot with a RAG pipeline indexing 5,000+ pages within an $80/month budget.

Led requirement gathering, backlog prioritization, and roadmap planning for a multi-country, multi-module travel platform across Japan, EU, and Southeast Asia. Authored BRDs/PRDs for multilingual mobile-first experiences and improved ML pricing accuracy by 18% by introducing structured hypothesis testing and A/B experimentation.

Built real-time operational dashboards for kitchen utilization, order velocity, waste, and equipment performance, supporting 120% revenue growth over two quarters. Improved order-to-payment accuracy by 18% via POS integrations and auto reconciliation, and reduced operational P&L costs by 23% through kitchen profitability optimization.

As the first technical hire, launched a modular travel platform in 9 months by defining architecture, establishing delivery processes, and leading a 10-member team. Increased conversion by 22% using A/B testing and built/maintained 8+ global platform integrations with API response times under 300ms.

Led vendor management, IoT product manufacturing coordination, and supply chain execution for kitchen automation development across India and USA deployments. Supported operational readiness and delivery planning for automation rollouts.

B.Tech. in Metallurgical Engineering and Materials Science at IIT Bombay. Transitioned from materials science to product and technology through self-directed learning and built proficiency in product management, AWS, SQL, and core machine learning/AI concepts.