Hi, I'm Abisheck B
Artificial Intelligence and Machine Learning Engineer specializing in Generative AI, LLMs, and full-stack AI applications. Passionate about building scalable, high-performance models and integrating intelligent systems into production-ready applications.
🧠 AI & Machine Learning Specialist | Solving Real-World Challenges
A highly motivated Computer Science Engineer and Machine Learning Practitioner dedicated to leveraging Artificial Intelligence to solve complex, real-world problems.
My expertise lies in the end-to-end lifecycle of ML model development: from data preprocessing and feature engineering to model training, optimization, and production deployment. I specialize in creating robust, scalable, and high-performance ML solutions.
Core AI/ML Capabilities 🚀
Machine Learning (ML): Deep experience with foundational algorithms including KNN, Support Vector Machines (SVM), Random Forest, and AdaBoost, alongside clustering techniques like K-Means and DBSCAN. Proven ability to select, fine-tune, and evaluate models for optimal performance.
Deep Learning (DL): Actively advancing expertise in Deep Learning architectures (e.g., CNNs, RNNs/LSTMs) using PyTorch to tackle intricate problems in areas like computer vision or sequence data analysis. (Optional: If you have specific DL projects, consider mentioning them here, e.g., "focusing on advanced tasks such as image classification and natural language processing.")
MLOps & Deployment: Proficient in deploying models for real-time applications using Python and integrating them into production environments. Currently focusing on model optimization, pipeline orchestration, and maintaining high-availability ML services.
Technical Stack 💻
ML/AI: Python, scikit-learn, PyTorch, Pandas, NumPy.
Data & Back-End Foundation (Full Stack): Strong background in building scalable backend systems using Java, Spring Boot, MySQL, and developing resilient REST APIs. This provides a unique perspective on integrating ML services into enterprise-level applications.
Key Enhancements Made:
AI Focus: Started with "AI & Machine Learning Specialist" to immediately signal your area of expertise.
Impact Statement: The first line clearly states your motivation: "leveraging Artificial Intelligence to solve complex, real-world problems."
Refined Terminology: Explicitly mentions the end-to-end lifecycle and MLOps concepts ("production deployment," "pipeline orchestration").
Deep Learning Specificity: Separated Deep Learning into its own bullet point, emphasizing PyTorch and specific DL architectures.
Bridging Skills: Highlighted the value of your Java Full Stack experience—it's not just a past skill, but a strength in "integrating ML services into enterprise-level applications."
Principles of Generative AI
Prompt Engineering
Artificial Intelligence Primer
Data Science Foundation
Statistical Inference using Python
Computer Vision 101
OpenAI GPT for Developers
Large Language Model Finetuning
Machine Learning with ETL Tools
Machine Learning Intern
Engineered and trained ML/DL models for 3+ real-world applications using PyTorch and TensorFlow.
Developed Hand Sign Detection (YOLO) and Resume Classifier, improving accuracy by 15%.
Worked on Generative AI and LLM-based solutions for business workflows.
Full Stack Development Intern
Developed and maintained full-stack web applications, reducing API latency by 10% by building robust RESTful
backends and dynamic frontends.
Implemented efficient database operations using JPA/Hibernate with MySQL, decreasing query time by 20%.
Designed scalable APIs and tested integration with Postman.
Contributed to backend logic and frontend features in an Agile environment..
Web Development Intern
Assisted in designing and developing 5 responsive websites using HTML, CSS, JavaScript, and Bootstrap.
Optimized web pages for performance and improved user experience, boosting page load speed by 25%.
Contributed to both front-end and back-end development, meeting all project timelines and client requirements.
AI Resume Job Looker (RAG Chatbot)
Developed a Retrieval-Augmented Generation (RAG) chatbot using LangChain and Flan-T5 to automate
resume-job fit analysis.
Reduced manual screening time by 40% by integrating Hugging Face Transformers for NLP-based similarity
ranking.
AI-Based ERP System with Predictive Analysis
Developed an AI-driven ERP platform automating staff/resource allocation with predictive analytics.
improving operational efficiency by 30% using Python & Streamlit.
Real-Time Hand Sign Detection (YOLOv8)
Built a real-time hand gesture recognition system using YOLOv8 and PyTorch, achieving 98% classification accuracy.
Deployed the model for real-time inference with optimized latency using OpenCV and TorchServe.
OCR-Enhanced RAG Chatbot
Developed an intelligent, context-aware chatbot capable of answering complex queries against unstructured documents.
it including scanned images and PDFs, by integrating Optical Character Recognition,a Natural Language Processing preprocessing pipeline.
Top Performer
Recognized as Top Performer during ML Internship at Cobra Softwares Inc (2025).
Best AI Project Award
Awarded for AI-Based ERP System using Predictive Analysis (2025).
Innovation Recognition
Hand Sign Detection using YOLO showcased at Adorn Web Solutions Demo Day (2025).
Runner-Up, CodeSprint 3.0
AI Automation Challenge (2024) – developed a workflow automation model.
LeetCode 300+
Solved 300+ DSA problems with a highest rating of 1,650.