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Rakesh Varipelly

@rakeshvaripelly

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Aspiring AI/ML engineer focused on NLP and real-time deep learning solutions.

India

Message

What I'm looking for

I seek an entry-level AI/ML role where I can apply NLP and deep learning skills, contribute to real-time projects, work cross-functionally, and grow through mentorship and impactful product work.

I am an aspiring AI and Machine Learning engineer with a strong foundation in computer science and hands-on experience building real-time NLP and deep learning projects. I have implemented transformer-based models, LSTM and ensemble approaches for classification tasks, and delivered end-to-end projects including an AI-powered English-to-Indian language translator and cryptography algorithm identification.

I combine practical ML skills with frontend and visualization abilities—developing interactive UIs with Streamlit, building dashboards in Power BI, and contributing technical content via a YouTube channel. I solve problems consistently (200+ coding challenges), enjoy learning cutting-edge technologies, and aim to build intelligent, production-ready systems.

Experience

Work history, roles, and key accomplishments

Current

AI / ML Intern

Current

aitechexplorer3

Nov 2024 - Present (11 months)

Created and managed a faceless YouTube channel producing educational content on AI tools and automation, growing audience engagement through consistent technical walkthroughs since Nov 2024.

Content Creation Python AI Tools Video Production SEO Streamlit Communication

Student Researcher

Chaitanya Bharathi Institute of Technology

Aug 2023 - Jun 2026 (2 years 10 months)

Conducted real-time NLP and deep learning projects including an English-to-Indian-language translator and cryptography-algorithm classifier, achieving multi-language support and ensemble-model improvements in accuracy.

Python TensorFlow PyTorch Hugging Face NLP Transformers Streamlit Model Ensembling

Data Analyst Intern

Zepto (project)

Built a Power BI dashboard analyzing sales performance and customer satisfaction, created DAX measures for KPIs (Total Sales, Average Ratings) and configured interactive visuals for stakeholder insights.