Amit Jadhav

I’m an AI/ML Engineer with 1+ year of experience building Large Language Model systems across Reinforcement Learning from Human Feedback, Retrieval Augmented Generation, and Prompt Engineering. I focus on creating high-quality training datasets, evaluating model outputs, and improving reasoning quality.

At Turing, I lead an AI/ML pod delivering rigorous SFT datasets and reliable ML pipelines. I’ve spearheaded RLHF alignment initiatives, improving AI code reasoning and problem-solving accuracy by 25%, while onboarding teammates and enforcing quality review standards.

I enjoy turning evaluation into action—designing and fine-tuning LLMs using curated datasets for complex algorithmic and natural language tasks. I also help optimize deployment processes to enhance scalability, ensuring solutions work reliably for global clients.

My project work spans benchmark and dataset engineering (Terminal-Bench/OS-Bench, Code Reasoning Datasets) as well as AI product development, including an AI-powered resume builder with automated PDF exports. I’ve also built multimodal fake news detection systems using RAG with BERT and VGG16, combining image/text features with external knowledge vectors for accurate, contextual assessments.