I build scalable software systems, AI-powered applications, and full-stack products focused on real-world problem solving. My work spans backend engineering, machine learning, computer vision, LLM applications, and production-ready deployment workflows.

📍 India
📧 Email: satyateja671@gmail.com
🌐 Portfolio: https://satyatejachukka.github.io/

• 🔹 Backend engineering with FastAPI, REST APIs, and scalable workflows
• 🔹 Full-stack application development using React + TypeScript
• 🔹 AI/ML systems including LLMs, Computer Vision, and Sequential Models
• 🔹 Dockerized deployments and production-ready architectures
• 🔹 Building practical software products with real-world impact

Contributed to an AI-powered badminton analytics platform focused on shot analysis, rally analytics, and match-performance insights from gameplay videos.

• Built automated Kaggle execution workflows by dynamically injecting generated match IDs into notebooks and triggering remote video-processing pipelines
• Integrated Kaggle and Google Drive automation workflows for source video retrieval, preprocessing, and processed video storage
• Worked on LSTM and dataset preparation for BiLSTM + Attention models for shot analysis, next-shot prediction, rally classification (aggressive, defensive, neutral), and winning probability estimation
• Trained ResNet and MobileNet-based court detection models using 200+ manually annotated gameplay frames, achieving 99.66% pixel accuracy
• Benchmarked inference performance across multiple resolutions for optimized real-time gameplay analysis workflows

🔗 Live Demo: https://wealthsync-lemon.vercel.app/
🔗 GitHub: https://github.com/SatyaTejaChukka/wealth_sync

Full-stack personal finance platform built with FastAPI, React, and PostgreSQL for transaction tracking, spending categorization, and financial analytics.

• Designed REST APIs using FastAPI, Pydantic, and SQLAlchemy for authentication, transaction management, and reporting workflows
• Built responsive dashboard interfaces with React and Vite for real-time financial insights and spending visualization
• Architected PostgreSQL schemas and Alembic migration pipelines for scalable financial data handling
• Containerized backend and frontend services using Docker and docker-compose for deployment and development workflows

🔗 GitHub: https://github.com/SatyaTejaChukka/interviewmaster

AI-powered mock interview platform that generates adaptive interview questions, topic-specific subtopics, and AI-based feedback using multiple LLM providers.

• Integrated Gemini, Claude, Groq, Mistral, and OpenRouter with automatic fallback handling and provider-level rate limiting
• Built adaptive interview workflows based on selected topics, difficulty levels, and focus areas
• Developed AI interview coach modes for behavioral interviews, DSA preparation, and system design practice
• Implemented provider selection, API key management, local persistence, and customizable user preferences

🔗 GitHub: https://github.com/SatyaTejaChukka/stroke-prediction

Machine learning web application for predicting stroke risk using FastAPI and Random Forest models.

• Built backend prediction APIs and integrated ML inference workflows for real-time predictions
• Applied preprocessing, feature engineering, and model evaluation techniques for improved prediction performance
• Dockerized and deployed the application using AWS Elastic Beanstalk, S3, and CloudFront

• Backend development and scalable API design
• LLM applications and RAG-based systems
• Dockerized deployment workflows
• Full-stack application architecture
• Machine learning deployment and inference pipelines

I’m interested in:

• 🚀 Software Engineering opportunities
• 🤖 AI / ML projects
• 🌐 Backend & full-stack systems
• 🧠 Open-source contributions
• 📈 Building impactful software products

📩 Feel free to connect or collaborate!