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AI Engineer with less than a year in Computer Vision, Machine Learning & Agentic AI Systems
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Assessing your cultural and operational fit
Highly motivated and results-oriented AI enthusiast with hands-on experience in Machine Learning, NLP, and Computer Vision. Proven ability to optimize model deployments, fine-tune large language models for tool-calling, and develop multi-agent AI systems for complex task execution. Possesses strong technical skills in PyTorch, Transformers, LangChain, and FastAPI, coupled with a solid foundation in cloud platforms like AWS and Google Cloud. Eager to contribute innovative solutions in Generative AI and AI systems.
Centurion University of Technology and Management
B.Tech · CSE
August 1, 2021 – June 30, 2025
C-DAC, Chennai - Ministry of Electronics and Information Technology, Government of India
Project Associate (Computer Vision)
February 1, 2026 – April 1, 2026
Chennai, Tamil Nadu, India
Gemma 3 Tool-Calling Fine-Tuning
June 24, 2026 – Present
Fine-tuned Gemma 3 to improve tool-calling capabilities by developing a custom chat template, preparing and optimizing training datasets, implementing response masking strategies, and resolving tokenizer and training pipeline issues. Evaluated model behavior across checkpoints and refined data composition to improve tool invocation accuracy and workflow adherence.
Autonomous Multi-Agent AI System
June 24, 2026 – Present
Designed and implemented a multi-agent AI system for autonomous task execution and research workflows, enabling structured task decomposition, tool execution, and iterative reasoning. Built modular agents (planner, executor using OpenClaw, critic, memory) with feedback loops and hybrid memory (short-term + vector DB) to improve contextual decision-making and output quality.
Retrieval-Augmented Generation(RAG) Based Document Helper
June 24, 2026 – Present
Developed a GenAI-powered document assistant using LangChain, FAISS DB, Hugging Face Sentence-Transformers and Gemini to deliver real-time answers from user-uploaded PDFs, with session persistence and intuitive UI via React/Bootstrap.
Computer Retail & Support Online Platform (Local Client)
June 24, 2026 – Present
Developed and deployed a full-stack web application according to client requirements using React, FastAPI, and MongoDB, with CD automation via GitHub-Cloud Build integration and hosting on Google Cloud Run.
Machine Learning in Production
Coursera
January 1, 2026 – Present
Introduction to AI and Machine Learning on Google Cloud
Coursera
September 1, 2025 – Present
Cultural Fit Analysis
The candidate demonstrates a strong interest in cutting-edge AI technologies, evidenced by projects in LLM fine-tuning, multi-agent systems, and RAG. The personal projects indicate a proactive and self-driven learning approach. The academic achievements and certifications further highlight a commitment to continuous learning and development, which aligns well with an innovative and fast-paced AI engineering environment. The range of technologies used across projects suggests adaptability and a willingness to explore different tools and platforms.
Soft Skills & Operational Fit
The candidate's project descriptions imply problem-solving, collaboration, and strategic thinking, which are crucial for an AI Engineer role. The diversity of projects suggests an ability to adapt to different technical challenges and work independently or as part of a team. However, direct evidence of these soft skills in a team setting is limited to project descriptions.