Hulash Chand
5+
Years ExpYears Exp
10+
Flagship ProjectsFlagship Projects
Data platforms, delivered.
I build the infrastructure that turns raw data into reliable intelligence. From pipeline orchestration in Airflow to production ML deployment on Kubernetes, my work spans the full stack of modern data engineering.
Trained in Data Science with Financial Technology at the University of Bristol, I bring both academic rigour and hands-on engineering to every system I design. I have built ETL pipelines processing millions of records, deployed XGBoost models with automated CI/CD, and architected real-time multiplayer systems with spatial databases.
Currently working as an AWS Consultant and Data Engineer, I specialise in cloud-native data platforms, MLOps infrastructure, and scalable AI systems. My work cuts across AWS, Azure, GCP, Spark, Python, and the modern ML stack.
Selected Work
Five projects spanning agentic AI architecture, production MLOps, generative diffusion fine-tuning, applied ML research, and systems-level interactive builds.
Selected Work
Five projects spanning agentic AI architecture, production MLOps, generative diffusion fine-tuning, applied ML research, and systems-level interactive builds.
Haeckel LoRA: Generative Diffusion on Kunstformen der Natur
A LoRA fine-tune of Stable Diffusion 1.5 trained on all 100 plates of Ernst Haeckel's Kunstformen der Natur: a 124-epoch run, an honest evaluation of where it converges and where it doesn't, and six novel specimens the model invented in a style it learned from scratch.