Open to opportunities

Rishabh Rathi

@rishabhrathi

Final-year AI/ML B.Tech student building machine learning, deep learning, NLP, and computer vision systems with explainable results.

India

Message

What I'm looking for

I’m seeking an AI/ML or Python Developer role where I can build and deploy ML pipelines using deep learning, NLP, computer vision, and explainable AI—converting practical research and experimentation into real-world applications.

I’m a final-year B.Tech student specializing in AI & ML (graduating 2026), focused on turning data into working models. I build end-to-end ML pipelines—from data preprocessing to deployment—using Python with TensorFlow and Scikit-learn.

Through my internships, I’ve delivered practical systems like an OCR-based invoice data extraction tool and a Flask deployment. I also completed research work in medical imaging AI, developing a Vision Transformer (ViT-B/16) brain tumor classifier and using explainable AI concepts to interpret results.

I enjoy tackling real-world problems with strong experimentation and evaluation. I built a customer churn prediction model using Random Forest and XGBoost, applying EDA, feature encoding, missing-value treatment, and SMOTE to improve performance for imbalanced data.

My work also extends to NLP and application-ready projects, including an NLP-based spam & ham classifier with TF-IDF and model benchmarking, plus a Flask-based movie recommendation system using collaborative and content-based filtering. I’m actively seeking an AI/ML or Python Developer role where I can apply deep learning, NLP, computer vision, and explainable AI to real-world products.

Experience

Work history, roles, and key accomplishments

Machine Learning Intern

Impressico Business Solution

Feb 2026 - May 2026 (3 months)

Built a customer churn prediction model using Python and scikit-learn with Random Forest and XGBoost on 7K+ telecom customer records. Used EDA, feature encoding, missing-value treatment, and SMOTE for imbalance, and selected Random Forest based on 5-fold cross-validation.

Machine Learning Churn Modeling Python scikit learn Random Forest XGBoost EDA Feature Encoding Missing Value Treatment SMOTE Decision Trees Cross Validation

Research Intern

NIT Silchar

Jan 2026 - May 2026 (4 months)

Trained and evaluated a ViT-B/16 brain tumor classifier on 7,023 MRI images (4 classes) using 5-fold cross-validation. Reported 99.94% training accuracy and 98.51% test accuracy.

Research Deep Learning Brain Tumor Classification MRI Image Classification Python Image Processing Cross Validation

Machine Learning Intern

Volition LLP

Nov 2025 - Dec 2025 (1 month)

Developed an OCR-based invoice data extraction system using Tesseract OCR and OpenCV, including custom Tesseract training and image preprocessing to handle diverse invoice layouts. Deployed the solution as a Flask web application and reported 87% extraction accuracy for structured metadata retrieval.

Machine Learning Tesseract OpenCV Python Image Processing Flask Computer Vision Deploying

Education

Degrees, certifications, and relevant coursework

Sikkim Manipal Institute of Technology

Bachelor of Technology, Artificial Intelligence and Machine Learning

Pursuing a Bachelor of Technology in Computer Science Engineering with a specialization in Artificial Intelligence and Machine Learning, expected to graduate in August 2026.