Eklavya Jumnani

Building end to end ML pipelines using MLflow, Prefect, and FastAPI across client projects. Contributing to industrial digital twin systems involving real time data and ML inference. Designing and delivering AI workshops to technical and business audiences.

Led the end to end refactoring of the security department's analytics codebase alongside the CISO, migrating 50+ legacy processes to cloud infrastructure on AWS. Owned the full lifecycle from architecture design and code rewrite to adding new functionality, CI/CD setup on GitLab, and Docker deployment to container registry. Delivered production grade pipelines in Python with PostgreSQL as the data layer.

Research assistant supporting a university team working on deploying open source LLMs on the FAU high performance computing cluster. Contributed to data preparation for model training including dataset merging, splitting, and formatting. Handled model evaluation, scripting, and infrastructure setup on Linux HPC environment.

Worked on legacy to cloud migration projects for enterprise clients including British Telecom. Contributed to infrastructure transition, log management using the ELK stack, scripting, and operational workflows within a delivery team.