Chirag Jha Email & Phone Number

India

• Developed and deployed a multi-agent model using Langchain and Langgraph for automating SEO keywordanalysis and blog creation, enhancing content generation efficiency.• Created and integrated tools such as a web scraper and SEO metric API, enabling data collection and real-timeSEO performance analysis.• Automated content creation processes by leveraging advanced LLMs, significantly reducing manual effort in bloggeneration.• Deployed backend infrastructure on AWS SAM… Show more • Developed and deployed a multi-agent model using Langchain and Langgraph for automating SEO keywordanalysis and blog creation, enhancing content generation efficiency.• Created and integrated tools such as a web scraper and SEO metric API, enabling data collection and real-timeSEO performance analysis.• Automated content creation processes by leveraging advanced LLMs, significantly reducing manual effort in bloggeneration.• Deployed backend infrastructure on AWS SAM CLI, ensuring scalable and reliable performance for themulti-agent systems and associated tools Show less

India

India

• Spearheaded software testing for industrial projects, ensuring functional integrity and user satisfaction.• Conducted meticulous WCAG checklist assessments, enhancing website accessibility and inclusivity.• Managed manual, regression, and sanity testing, assuring top-tier performance and seamless user experiences.• Advocated software quality by validating changes and upholding product excellence during development.

India

• Implemented the YOLO algorithm and object detection principle, focusing on convolutional neural networksand anchor-based methods.• Curated datasets for training, ensuring real-world representation and implementing data augmentation techniques.• Executed YOLO architecture using TensorFlow/PyTorch, optimizing model performance throughhyperparameter tuning and selecting appropriate YOLO variants.• Evaluated model performance using metrics like precision and recall… Show more • Implemented the YOLO algorithm and object detection principle, focusing on convolutional neural networksand anchor-based methods.• Curated datasets for training, ensuring real-world representation and implementing data augmentation techniques.• Executed YOLO architecture using TensorFlow/PyTorch, optimizing model performance throughhyperparameter tuning and selecting appropriate YOLO variants.• Evaluated model performance using metrics like precision and recall, iteratively fine-tuning the YOLO model toimprove object localization and detection. Show less