Siddharth Panicker Email & Phone Number

As Software Developer at Brevitaz, I've had the privilege of making meaningful contributions to two impactful projects. Specializing in Java and Spring for backend development, with expertise in REST, GraphQL, Elasticsearch and GitLab CI. Currently transitioning towards Full Stack development, proficient in React and JavaScript. Project Domain: Supply chain application Backend Development Expertise: - Collaborated in designing and implementing backend services and APIs. - Proficient in developing REST and GraphQL web services using JAVA and Spring. - Skilled in JAVA applications development, incorporating technologies such as Spring, Apache Kafka, and ElasticSearch. - Executed API testing using JUnit and Mockito for unit testing. - Conducted integration tests to ensure seamless communication and functionality across components. Infrastructure Operations and DevOps Tasks: - Automated build pipeline by implementing CI/CD using GitLab Database Management: - Gained hands-on experience with databases like Elasticsearch.Project Domain: Sales enablement applicationCurrently exploring the path of becoming a Full Stack Developer and enhancing my programming skills in frontend development. - Extensive experience in Java development, utilizing JSP, Struts, and Servlets to create robust and scalable backend systems. - Skilled in crafting modern and responsive user interfaces using JavaScript, React, and CSS. - Proactively identify and address challenges, implementing effective solutions to optimize application performance.

Starting as a Software Developer trainee at Brevitaz, here's what I've gained:The training equipped me with valuable hands-on experience utilizing frameworks like Spring Boot and managing databases like MySQL and Elasticsearch. I enhanced my skills in writing clean and efficient code, embracing design principles like SOLID and Design Patterns. Additionally, I gained proficiency in version control tools like Git.

-The task in hand was for object detection and it can betrained as we wish with the help of images and the webinterface, then with the machine learning algorithm it candetect the objects for which it is trained for and annotatesthe object with the label of it. -The project has a web interface which is responsible forannotating the images and providing the labels for it so thatit can we recognized as that object in that image. -After the image data set being ready, we convert it to aformat, which is readable for the algorithm.