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AI Research Engineer with less than a year in Deep Learning & Multimodal AI
AI Research Engineer with strong foundations in deep learning, Python, and PyTorch, with hands-on experience building end-to-end machine learning systems. Proficient in transformer architectures, large language models (LLMs), Vision-Language Models (VLMs), and generative AI. Experienced in RAG architectures, multimodal learning, and production ML pipelines. Strong experimental and research mindset - comfortable with literature surveys, model benchmarking, ablation studies, and rigorous experiment tracking. Seeking to apply deep learning expertise to multimodal geospatial AI and remote sensing research.
Adhiyamaan College of Engineering
B.E. · Computer Science and Engineering
August 1, 2021 – June 30, 2025
Makelabs
UI/UX & Data Intern
June 1, 2024 – July 1, 2024
Krishnagiri, Tamil Nadu, India
Inspire Softech Solutions
Data Science Intern
December 1, 2023 – January 1, 2024
Chennai, Tamil Nadu, India
Hospital Management RAG System
January 1, 2025 – June 1, 2026
Built an autonomous AI agent combining retrieval-augmented generation (RAG) with LLM reasoning and transformer-based embeddings for natural-language querying of structured hospital data, eliminating SQL dependency for non-technical users. Implemented end-to-end data ingestion, preprocessing, integrity verification, and governance workflows to ensure reliable, production-safe model inputs. Validated model accuracy against structured ground-truth datasets using Scikit-learn evaluation metrics, applying rigorous benchmarking before deployment – consistent with research validation practices.
View ProjectPropPredict AI ML Prediction Engine
January 1, 2025 – June 1, 2026
Developed a production ML system using XGBoost and Random Forest with feature engineering and statistical analysis for high-accuracy property price and ROI prediction from high-dimensional datasets. Deployed the full ML lifecycle – from model training, hyperparameter tuning, and ablation-style evaluation to Streamlit Cloud via GitHub CI/CD – demonstrating experiment-driven, repeatable model development. Integrated an NLP-powered multimodal chatbot interface enabling natural-language querying of model predictions, bridging deep learning outputs with user-facing interaction.
View ProjectPersonal Data Analyst AI Bot - Automated Reporting Engine
January 1, 2025 – June 1, 2026
Built an AI-powered automated reporting engine using LLMs and NLP that reduced manual analytics effort by 40%, deployed via Flask REST API for real-time on-demand report generation. Designed executive-ready visualizations and plain-language summaries translating complex model outputs for non-technical stakeholders – practiced clear research presentation skills.
View ProjectDubai Real Estate Market Pulse BI Dashboard
January 1, 2025 – June 1, 2026
Engineered ETL pipelines to clean and structure raw UAE property datasets across 4 districts into a reliable analytical source, then built an interactive BI dashboard with KPI tracking, ROI analysis, and investment scoring. Applied statistical analysis and visualization techniques using Pandas, NumPy, and Plotly to surface actionable investment intelligence – demonstrating data-driven insight generation from large-scale structured datasets.
View ProjectArtificial Intelligence
Simplilearn
June 1, 2026 – Present
Data Analytics Job Simulation
Deloitte
June 1, 2026 – Present
Prompt Engineering
Great Learning
June 1, 2026 – Present
Self-Study: Vision Transformers (ViT), Diffusion Models, GANs, multimodal learning (CLIP, BLIP), remote sensing fundamentals, SAR/EO imagery concepts
Unknown
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's projects showcase a strong alignment with the target role of AI Research Engineer, particularly in areas like RAG systems, multimodal AI, and production ML. The diversity of projects, from hospital management to real estate prediction and automated reporting, indicates a broad interest and adaptability in applying AI solutions across different domains. Their self-study in advanced topics like Vision Transformers, Diffusion Models, and multimodal learning demonstrates a proactive and continuous learning mindset, which is crucial for a research-oriented role. However, the experience is primarily from personal projects and internships, which might require more structured team collaboration experience in a corporate research setting.
Soft Skills & Operational Fit
The candidate demonstrates strong technical communication skills through preparing structured analytical reports and translating complex model outputs for non-technical stakeholders. Their project descriptions highlight an experiment-driven, repeatable development approach and rigorous benchmarking, indicating a methodical and quality-focused operational fit. The focus on autonomous agents and production ML systems suggests an ability to work independently and deliver deployable solutions.