Onkar Jinde

• Monitored security alerts generated by SIEM systems to ensure real-time threat detection. • Analyzed security incidents to identify vulnerabilities and unauthorized activities, enhancing overall security posture. • Collaborated with IT teams to implement and configure security solutions, streamlining incident response processes. • Documented security incidents and created tickets for effective tracking and resolution.

Currently developing an advanced, micro-service-based face detection system leveraging NVIDIA Jetson and DeepStream SDK in a cloud-native environment. Key aspects of the ongoing project include: • Implementing a microservices architecture for scalable face detection • Utilizing NVIDIA DeepStream pipeline for efficient video analytics • Integrating pre-trained face detection models optimized for Jetson platform • Developing real-time face detection targeting 25-30 FPS performance • Applying cloud-native principles for deployment and scaling • Creating API endpoints for seamless integration with other services • Developing a frontend interface to display system logs and metrics • Implementing remote website access for real-time video stream monitoring • Establishing CI/CD pipelines for streamlined development and deployment • Addressing edge computing and network streaming challenges in a distributed system Technologies: NVIDIA Jetson, DeepStream SDK, Docker, Kubernetes, TensorRT, OpenCV, Python, React.js, WebRTC This project is providing hands-on experience with edge AI, computer vision, cloud-native technologies, and full-stack development, enhancing my skills in modern software engineering and AI application deployment.

As a data engineer intern working on various big -data technologies and Responsible for creating complete test cases, test plans, test data, and reporting status ensuring accurate coverage of requirements and business processes