AI Research Engineer with less than a year in Machine Learning & AI Agents
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Highly motivated and results-oriented professional with a strong foundation in Computer Science and a passion for Artificial Intelligence. Possessing hands-on experience in building data science solutions, developing RAG AI agents, and implementing multi-modal RAG systems. Proficient in Python, Machine Learning, NLP, and cloud platforms like Azure. Eager to contribute to innovative projects in the AI/ML domain.
Rajasthan Technical University
Bachelor of Technology · Computer Science
January 1, 2022 – January 1, 2026
Xebia
Data Science Apprentice
December 1, 2025 – Present
India
AU Ignite Future Skills Centre
AI - Data Scientist Trainee
August 1, 2025 – November 1, 2025
India
Linuxworld Informatics Pvt. Ltd.
Machine Learning Trainee
June 1, 2024 – August 1, 2024
India
AI Agent for Multi-Provider Knowledge Retrieval
June 24, 2026 – Present
Built a Python-based agentic AI system using Azure OpenAI (gpt-4.1-nano) to orchestrate multi-step tool workflows across Microsoft, AWS, and GCP MCP servers for real-time documentation retrieval. Designed a query classification engine to route user intent before LLM invocation, reducing tool misfires and improving response accuracy. Deployed a fault tolerant FastAPI backend with async parallel tool execution and error isolation, along with a React UI featuring a custom Markdown renderer.
Advanced Multi-Modal RAG System
June 24, 2026 – Present
Built a multi-modal RAG system for PDFs, DOCX, Excel, and images to extract insights from unstructured data. Developed hybrid retrieval pipeline (FAISS + BM25 + reranking) achieving 91% accuracy and 0.91 Precision@4. Implemented LLM-based caching reducing cost by 90% and achieving 50ms response time. Enabled natural language to SQL conversion for querying structured data.
Student Performance Prediction
June 24, 2026 – Present
Built a complete machine learning pipeline to predict student's math scores based on features such as gender, race, parental education, lunch type, and test preparation course. Deployed the model using Streamlit, creating an interactive web app that allows users to input student details and receive predictions.
View ProjectMachine Learning
LinuxWorld Informatics
June 1, 2026 – Present
Gen AI & ML
Prepzee Learning Solutions Pvt. Ltd.
June 1, 2026 – Present
Data Science
Oracle Cloud Infrastructure
June 1, 2026 – Present
Python
Learn and Build
June 1, 2026 – Present
Generative AI Engineer Associate
Databricks Certified
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's projects and experience demonstrate a strong interest and practical application in cutting-edge AI technologies, particularly Generative AI and agentic systems. This aligns well with an 'AI Research Engineer' role, which typically values innovation, problem-solving, and continuous learning. The diversity of projects (multi-provider agents, multi-modal RAG, classical ML prediction) shows a broad interest in AI applications. The current role as a Data Science Apprentice at Xebia further reinforces a commitment to professional development in the AI/ML space.
Soft Skills & Operational Fit
The candidate's resume highlights 'Communication, Team Collaboration, Presentation, Documentation, Problem Solving' as soft skills. Project descriptions indicate an ability to articulate technical solutions and deploy user-facing applications, suggesting good operational fit for roles requiring end-to-end development and communication.