🚀 Software Engineer | Cloud-Native Developer | Intelligent Systems Architect

I build scalable software solutions that leverage the power of AI and ML for enhanced user experiences and operational efficiency. With over 5 years of experience, I specialize in designing and deploying cloud-native applications, microservices architectures, and intelligent systems. My work seamlessly integrates backend development with advanced ML models, ensuring robust and efficient applications.

🎓 Education: University of Florida Graduate

• Cloud-Native Application Development: Architected and deployed microservices using FastAPI, Docker, and Kubernetes for secure and scalable systems.
• Backend Engineering: Implemented RESTful APIs and optimized query performance with PostgreSQL and materialized views for high-efficiency data access.
• Intelligent Systems Integration: Incorporated advanced ML models into production systems, leveraging PyTorch and Huggingface.
• DevOps & CI/CD: Established CI/CD pipelines using GitHub Actions, Terraform, and Docker, enhancing deployment speed and system reliability.
• Monitoring & Observability: Deployed monitoring and alerting solutions using Prometheus and Grafana to ensure high availability and performance.

• 🎤 Conference Speaker & Attendee: Active participant at PyCon US and other tech conferences
• 👥 Tech Community Builder: Engaging with developer communities and sharing knowledge
• 🌟 Mentorship: Contributing to the growth of aspiring developers

• Programming Languages: Python, SQL, Bash
• Frameworks & Tools: FastAPI, Docker, Kubernetes, MLflow, DVC
• Cloud & DevOps: Azure, AWS, GitHub Actions, Terraform, Prometheus, Grafana
• Database Systems: PostgreSQL, MongoDB
• Machine Learning & AI: PyTorch, Huggingface, Langchain, OpenAI API

• Cloud-Native Microservices Platform: Built REST API-based microservices with FastAPI, deployed using Docker and Kubernetes, enabling secure data access for research applications.
• Inventory Intelligence System: Developed intelligent inventory tracking using computer vision and dual-camera depth analysis, deployed on JetsonOrin and RaspberryPi.
• Data Integration Pipelines: Designed scalable ETL pipelines for data preprocessing and transformation, optimizing embeddings for NLP applications.
• Predictive Analytics Engine: Engineered predictive models that identified high-growth products, driving strategic business decisions and operational efficiency.

• Enhanced system scalability and security by designing cloud-native microservices architectures.
• Reduced deployment time by 30% through efficient CI/CD pipelines and cloud infrastructure automation.
• Achieved over 97% accuracy in intelligent vision systems, driving impactful business solutions.

• LinkedIn: Srisharanya Injarapu
• Email: [injarapusrisharanya@gmail.com]
  Explore my repositories and connect for collaborations in Cloud-Native Applications, Intelligent Systems, or Backend Development!