Available for opportunities
Hi, I'm Akash
AI/ML Engineer & Full-Stack Developer
Passionate about building intelligent systems with RAG, LLMs, and autonomous agents. I specialize in creating scalable solutions that leverage AI to solve real-world problems. Currently exploring autonomous code repair and multi-modal document intelligence.
📍 Bangalore, India
✓ B.E. AI & Data Science Graduated (2025)
💼 Open to AI/ML & Full-Stack opportunities
GET TO KNOW ME
About Me
I'm a detail-oriented AI/ML Engineer and Full-Stack Developer with hands-on experience building intelligent systems through academic projects and professional internships. My passion lies in creating scalable, data-driven solutions that leverage cutting-edge AI technologies.
I specialize in Retrieval-Augmented Generation (RAG), Large Language Models, LangGraph, and autonomous agents. Recently, I've been exploring how to automate the development workflow through intelligent code analysis and generation.
Beyond coding, I love collaborating with teams, solving complex problems, and staying updated with the latest advancements in AI and machine learning. I'm driven by the opportunity to build solutions that make a real impact on real-world challenges.
Quick Facts
Location
Bangalore, India
Focus
AI/ML & Full-Stack
Experience
Internship + Projects
Status
Graduated 2025
PROFESSIONAL JOURNEY
Experience
Data Analyst Intern
CSIR4PI, NAL (National Aerospace Laboratories)
Sep 2024 – Dec 2024
Processed 10+ years of CHIRPS high-resolution rainfall data using Python, xarray, and pandas. Engineered predictive rainfall models using Random Forest Regression, improving forecast accuracy by 12%. Built and deployed geospatial visualizations (heatmaps, trend plots, maps) for climate analysis research.
Key Achievements
- →Processed 10+ years of rainfall data (2012–2023)
- →Improved forecast accuracy by 12%
- →Built geospatial visualizations for research
SHOWCASE
Featured Projects
Building intelligent systems that push boundaries
Agentic RAG with Serper API & Multi-Modal Processing
Advanced AI-powered document intelligence system with multi-modal PDF processing, semantic search, and agentic retrieval workflows. Features real-time interaction with 50+ MB of indexed data.
Key Highlights
- •Multi-modal pipeline: text, images, tables extraction from PDFs
- •Semantic chunking with embeddings via Ollama nomic-embed-text
- •Agentic retrieval: query rewriting, parallel searches, response quality loop
- •Real-time dark mode interface with file uploads
Tech Stack
AutoPR – Autonomous Pull Request Generation & Code Repair
MVP of an autonomous GitHub agent that analyzes codebases, detects failing tests, generates fixes using LLMs, and automatically opens validated Pull Requests.
Key Highlights
- •Self-correcting LLM pipeline with git-diff validation & syntax checking
- •Modular workflow: Analyzer → Suggester → Validator → Publisher
- •GitHub Actions integration for cloud-based automation
- •Up to 80% reduction in manual debugging time
Tech Stack
SKILLS & EXPERTISE
Tech Stack
Comprehensive toolset for building intelligent solutions
Programming & Querying
Web & Backend
AI/ML & Data
Tools & Platforms
Concepts & Patterns
ACADEMIC BACKGROUND
Education
B.E. Artificial Intelligence and Data Science
CMRIT College, Bangalore
✓ Graduated
CGPA: 7.73 / 10
Comprehensive coursework in artificial intelligence, machine learning, data science, software engineering, and database management. Built a strong foundation in algorithms, data structures, and modern development practices with hands-on experience in building intelligent systems.
Relevant Coursework
- • Machine Learning & AI
- • Data Science & Analytics
- • Database Management Systems
- • Software Engineering
- • Web Development
- • Advanced Algorithms
Certifications
- ✓ Machine Learning with NumPy, Pandas, Scikit-learn (Educative)
- ✓ Generative AI Workshops
- ✓ Software Development Best Practices