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Adityaraj B.

Adityaraj B.

Generative AI · Entry-level

Available profile

Professional Overview

I’m Adityaraj Belhe, an AI engineer and researcher with a strong foundation in generative AI, prompt engineering, and intelligent automation. Over the past few years, I’ve actively contributed to AI-driven projects that span diverse domains including education, healthcare, therapy, and enterprise automation. My technical skill set includes working with LLMs, RAG pipelines, agentic AI, computer vision, and custom deep learning models. I’m particularly passionate about designing scalable, real-world AI systems that are optimized even for constrained hardware.Currently, I serve as an AI Engineer for a Peruvian university, where I’ve helped develop a virtual health sciences simulator and automated grading systems using sentence transformers — positively impacting over 500 students and faculty. I’ve also built emotion-aware therapy assistants using DistilBERT and RAG, and contributed to medical imaging research by building CNN-based MRI classifiers that outperformed leading transfer learning methods.Beyond my technical work, I enjoy simplifying complex problems and collaborating across domains. My goal is to bridge business understanding with applied AI to build systems that are useful, ethical, and robust. I thrive in fast-moving environments where I can continuously learn and contribute meaningfully. My future interests lie in building LLM-native automation tools and scaling agentic AI workflows across industries.

Areas of Expertise

computer vision

Develop image recognition, object detection, video analysis, and multimodal AI systems for real-world applications.

NLP & Prompt Engineering

Build natural language processing systems, fine-tune large language models, and craft reliable production prompts for AI-powered products.

AI & Machine Learning Engineers

Design, train, and ship production ML models — from data pipelines to model inference at scale. Covers supervised learning, neural networks, LLM integration, and model optimisation.

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