Open to opportunities

Ramu japu

@ramujapu

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Computer Science graduate building end-to-end AI-powered NLP and ML systems.

India

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What I'm looking for

I’m looking for an entry-level AI/ML role where I can build LLM/NLP systems end-to-end, ship deployed pipelines, and validate results with strong evaluation—while prioritizing explainability and reproducible documentation.

I’m a final-year Computer Science graduate with hands-on experience building AI-powered systems, including NLP classifiers, RAG pipelines, and deployed ML applications. I enjoy owning problems end-to-end—spotting friction, prototyping, validating with data, and documenting everything for reuse.

I’m fluent in LLMs and AI workflow design, and I translate model outputs into measurable results using metrics like F1, precision, and recall. I focus on explainability, compute trade-offs, and building pipelines that are structured, reproducible, and easy for others to trust.

In my projects, I built a news bias classification system from scratch using Sentence Transformers, embeddings, and a centroid-based cosine similarity approach. I also shipped an interactive PCA dimensionality reduction web app with Streamlit so non-technical users could explore model behavior and variance visually, not just “run an algorithm.”

Experience

Work history, roles, and key accomplishments

News Bias Classifier

News Bias Classification System

May 2026 - Present (1 month)

Built an NLP news political-bias (Left/Center/Right) classification system from scratch, owning the full pipeline from preprocessing to evaluation. Implemented Sentence Transformer embeddings and a centroid-based cosine similarity classifier while validating with precision, recall, and F1.

Sentence Transformers Embeddings Cosine Similarity Centroid scikit learn data preprocessing Model Evaluation (F1 Precision Recall)

PCA Dimensionality Reduction

PCA Dimensionality Reduction Project

Sep 2025 - Present (9 months)

Engineered an end-to-end PCA ML pipeline with data standardisation, PCA application, and variance visualization. Shipped as an interactive Streamlit app so non-technical users could test the workflow and understand principal components and feature behavior.

scikit learn Streamlit Feature Importance Interpretation ML Pipeline Engineering

Education

Degrees, certifications, and relevant coursework

Sreenidhi Institute of Science and Technology

Bachelor of Technology (B.Tech), Computer Science Engineering

2022 - 2026

Grade: GPA: 8.24 / 10

B.Tech in Computer Science Engineering at Sreenidhi Institute of Science and Technology (Hyderabad) from 2022 to 2026. Completed relevant coursework in AI, Machine Learning, Deep Learning, NLP, LLMs, Generative AI, and DBMS.