Get to know me better
My story, values, and what drives me to create innovative solutions
Hello, I'm Sibi Krishnamoorthy
Applied AI & Backend Engineer specializing in deploying low-latency AI architectures, FastAPI microservices, and robust PyTorch pipelines. I bridge the gap between raw machine learning research and high-performance backend systems.
More About Me
Introduction
introI build production-grade AI systems and the high-performance backend infrastructure required to serve them. As an Applied AI & Backend Engineer, my focus is bridging the gap between raw machine learning research and scalable, secure enterprise software. Rather than just training models in notebooks, I specialize in deploying low-latency microservices with FastAPI, Redis, and PyTorch, alongside autonomous Agentic AI workflows (RAG & LangGraph). From modernizing legacy monoliths to engineering zero-trust authorization systems and Vision-Language analytics, I thrive on vibe coding and solving complex problems from first principles.
My Journey
storyMy journey in data science began during my undergraduate studies at Annamalai University, where I developed a strong interest in machine learning and data-driven systems. Through internships at CodSoft and CodeClause, I translated this passion into practice by building and deploying real-world AI solutions, continuously sharpening my skills through hands-on projects and research.
Core Values
valuesI prioritize clean design, reproducible results, and scalable solutions. I value precision, continuous learning, and engineering systems that are both reliable and performance-driven. My work is focused, data-centric, and impact-oriented.
My Journey
Bachelor of Engineering
Annamalai University • Tamil Nadu, India
Pursuing a Data Science–focused B.E. with core training in ML, DL, big data, and algorithms, complemented by hands-on internships and active tech community involvement.
Higher Secondary Education
Hindu Higher Secondary School • Tamil Nadu, India
AI Intern
CodSoft, India • Remote
Contributed to production-ready machine learning solutions for classification problems using deep learning frameworks and deployment tools.
- Designed and trained deep learning models using PyTorch and TensorFlow
- Developed end-to-end ML pipelines with MLOps practices
- Deployed models via FastAPI and Streamlit for interactive inference
- Participated in literature reviews and adapted open-source research
Data Science Intern
CodeClause, India • Remote
Built predictive models for financial fraud detection using advanced feature engineering and iterative model refinement.
- Developed and evaluated fraud detection models using ensemble methods
- Applied hyperparameter tuning and data preprocessing for performance gain
- Visualized fraud patterns using EDA and customized dashboards
AI Developer
AkaiSpace
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