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AI Engineer with less than a year in Machine Learning & Data Science
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Assessing your cultural and operational fit
AI enthusiast and Android Developer Intern with hands-on experience in building full-stack applications, integrating LLM-powered agentic components, and developing data-driven platforms. Skilled in Python, machine learning frameworks like TensorFlow and PyTorch, and cloud platforms including Firebase and AWS. Possesses a strong foundation in data preprocessing, visualization, and deployment, with a focus on ensuring robust, crash-free applications.
Sai Vidya Institute of Technology
Bachelor of Engineering · Computer Science and Engineering
August 1, 2022 – June 30, 2026
MindMatrix.io
Android Developer Intern
February 1, 2026 – May 31, 2026
Bengaluru, Karnataka, India
LaunchPad AI
February 1, 2026 – June 1, 2026
An Al-native application and autonomous multi-agent platform transforming a startup idea into market research, architecture, production-ready code, and ML-driven revenue forecasts. Designed Al agent planning and tool-use architecture using LangGraph and LangChain; built on FastAPI + React with WebSocket streaming, PostgreSQL persistence, and a self-correcting Critic Agent (LLM scoring 0.0–1.0) with LangGraph retry routing, grounded by a RAG pipeline (ChromaDB + OpenAI embeddings). Forecasting engine combines regression models (Facebook Prophet, XGBoost) and LSTM for zero-historical-data projections, with data cleaning and feature engineering via Pandas/NumPy.
View ProjectMultimodal Surveillance System for Intelligent Security Monitoring
June 1, 2025 – June 1, 2025
A real-time Al surveillance platform detecting fire, intrusion, explosion, accidents, and smoke from live feeds using parallel deep learning. Fused YOLOv11, 3D-CNN + LSTM action recognition, and CNN emotion recognition via an Adaptive Fusion Engine with Temporal Validation (65% confidence across 5 frames). Threat detection triggers an audio alarm and instant SMS/email notifications via Twilio. Events logged in MongoDB and streamed live via Flask + React dashboard.
View ProjectEV Charging Analytics Platform
March 1, 2025 – March 1, 2025
An interactive ML platform tracking EV infrastructure usage, forecasting grid demand, and clustering patterns across 457 charging stations. Built a multi-page Streamlit app with Plotly dashboards and a predictive pipeline combining Facebook Prophet with Histogram Gradient Boosting and Random Forest regressors — isolating 4 station behavioural personas via K-Means and PCA.
View ProjectRetail Inventory and Sales Analytics Platform
October 1, 2024 – October 1, 2024
A full-stack retail dashboard providing real-time inventory visibility, Al-driven demand forecasting, and automated restock alerts. Built 8+ interactive Streamlit dashboards covering inventory tracking, expiry monitoring, and sales funnels; integrated Facebook Prophet forecasting, an optimized MySQL query layer, SMTP restock alerts, and a PDF report generator with login-based auth.
View ProjectSpoken Keyword Spotting System
September 1, 2024 – September 1, 2024
A lightweight keyword classification system built with a hybrid CNN-SVM pipeline (TensorFlow, Scikit-learn) using Librosa MFCC and mel-spectrogram features, trained on Google Speech Commands. INT8 quantization reduced model size by 75% and latency by 40%, achieving a 0.98 F1-score across 10 keyword classes on edge devices.
View ProjectData Analytics with Python
NPTEL, IIT Roorkee
January 1, 2026 – Present
Artificial Intelligence Fundamentals
IBM SkillsBuild
January 1, 2025 – Present
Python Data Analysis
Rice University, Coursera
January 1, 2025 – Present
Networking and Cloud Computing
Microsoft, Coursera
January 1, 2025 – Present
Cultural Fit Analysis
The candidate's portfolio showcases a strong interest in AI and machine learning, aligning well with an AI Engineer role. The diversity of projects, from retail analytics to multimodal surveillance and agentic AI platforms, demonstrates a broad technical curiosity and ability to apply AI in various domains. However, the candidate's experience level (0 years) and current enrollment in a bachelor's degree program suggest a junior profile, which might not fully align with a senior AI Engineer role requiring extensive industry experience and leadership.
Soft Skills & Operational Fit
The candidate's project descriptions indicate a proactive approach to problem-solving and a strong drive for learning new technologies. The internship experience highlights full development lifecycle ownership, UI/UX design, testing, and documentation skills, suggesting good operational fit. Participation in code reviews and version control indicates an understanding of collaborative development practices.