As an LLMOps Engineer, I specialize in deploying, managing, and optimizing large language models (LLMs) in production environments. My work involves developing Python code, architecting scalable systems, and automating CI/CD pipelines to streamline model deployment and operations. Key contributions include:• Python Development: Created and optimized Python scripts for training, fine-tuning, and deploying custom LLMs, enhancing their performance and applicability.• Pipeline Automation: Developed multi-branch CI/CD pipelines using Jenkins and Ansible, reducing deployment time by 30% and ensuring seamless model integration.- Model Optimization: Led initiatives to improve LLM accuracy and efficiency, managing the conversion and retrieval of large-scale document datasets.• Infrastructure Scaling: Implemented cloud-based scaling solutions and managed GPU clusters, ensuring high availability and optimal model performance.• Collaboration: Promoted best practices in version control and code reviews, contributing to multiple GitHub repositories for robust and maintainable codebases.• Real-time Data Integration: Integrated LLMs with MongoDB for real-time data processing, developing chatbot interfaces and APIs for enhanced user interaction.

Work involves:• Provisioning automated CI, CD pipelines and creating highly reliable, secure & scalable infrastructure.• Creating a custom toolkit to support the engineering team.Work involves: • Creating a custom toolkit to support the engineering team.

YCombinator'15 & Google Launchpad funded company . Worked on creating secure reliable infrastructure and implementing infrastructure as code , managing Kubernetes cluster and do security testing and incident response .YCombinator'15 & Google Launchpad funded company . Worked on creating secure reliable infrastructure and implementing infrastructure as code , managing Kubernetes cluster and do security testing and incident response .