Riteesh Thiruveedhula

I’m an AI/ML undergraduate actively interning as an AI Engineer, focused on shipping end-to-end AI—from data ingestion and feature engineering to deployment. I care about reliability, interpretability, and explainable decision-making in real workflows.

In my Blue Planet internship, I built a candidate-job matching pipeline by engineering 25+ candidate/role features and training supervised ML classifiers, improving match prediction across 1,000+ candidate profiles. I also cleaned and standardized 5,000+ recruitment records, cutting data-preprocessing turnaround time by 40% through better validation and standardization.

I’ve led teams and delivered production-minded ML projects, including Telugu-language dataset building for Indic LLM experimentation (50,000+ validated samples) and adaptive AI product development during 24-hour hackathons. My work spans NLP, LLMs, and computer vision/OCR, with a strong emphasis on getting models into usable tools (APIs, dashboards, and Streamlit apps).

I published a first-author IEEE CCIC 2026 paper on feature-based AI-generated text detection, achieving 96% accuracy using attention-based fusion of handcrafted linguistic features and DistilBERT embeddings. I’m currently looking for software/ML engineering roles where I can build reliable, explainable, production-grade AI systems and partner closely with product stakeholders.