AI Engineer with less than a year in Machine Learning & Fullstack Development
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Highly motivated and results-driven AI Engineer with a strong foundation in Python, Machine Learning, and full-stack development. Possessing 4 months of internship experience in Android app development with Gemini 1.5 integration and extensive project work in multi-agent AI platforms, multimodal surveillance systems, and data analytics. Eager to apply deep learning, generative AI, and modern web technologies to solve complex problems and drive innovation.
Sai Vidya Institute of Technology
Bachelor of Engineering · Computer Science and Engineering
January 1, 2022 – January 1, 2026
MindMatrix.io
Android Developer Intern
February 1, 2026 – May 1, 2026
Bengaluru, Karnataka, India
LaunchPad AI
February 1, 2026 – Present
An autonomous multi-agent platform transforming a startup idea into market research, architecture, production-ready code, and ML-driven revenue forecasts. 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 Facebook Prophet, XGBoost, and LSTM for zero-historical-data projections.
View ProjectMultimodal Surveillance System for Intelligent Security Monitoring
June 1, 2025 – Present
A real-time AI 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 – Present
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 – Present
A full-stack retail dashboard providing real-time inventory visibility, AI-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 and admin management.
View ProjectSpoken Keyword Spotting System
September 1, 2024 – Present
A lightweight keyword spotting system built with a hybrid CNN-SVM pipeline 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 passion for AI and machine learning, with a diverse range of personal projects that align well with an AI Engineer role. The projects demonstrate initiative, self-direction, and a willingness to tackle complex problems independently. The use of various technologies and frameworks across projects indicates a broad technical curiosity and adaptability, which are valuable traits for cultural fit in an innovative environment.
Soft Skills & Operational Fit
The candidate's project descriptions indicate strong problem-solving skills and a proactive approach to learning and applying new technologies. The detailed project descriptions suggest good communication of technical concepts. The breadth of projects implies adaptability and a strong drive for continuous learning, which are positive indicators for operational fit in a dynamic AI engineering role.