Hi, I am Suraj Parmar, currently working as a Machine Learning Engineer at a medical-legal start-up in Toronto. Where I am managing the cloud infrastructure, building and scaling agentic document processing pipelines that can scales to hundreds of customers per day.
Previously, I worked at a healthcare start-up, SpassMed in Toronto where I have worked on projects involving statistical and deep learning based forecasting and classification models. Built and deployed efficient Retrieval Augmented Generation (RAG) pipelines in completely offline environments. Published papers on the topic of early Sepsis detection.
My master's thesis was on the topic of "Utilizing Deep Learning for Enhancing Performance on Encrypted Stock Market Data". The goal was to extract robust and meaningful representations for Numerai datasets to improve the GBDT baseline model. I have been researching on the Numerai datasets for financial data. My main focus right now is Transformers on cross-sectional asset prediction involving self-supervised learning. Can read more about it on my blog.
I previously interned at Zujo, a Computer Vision start-up in India, and later worked at RealAdvisor as a Data Scientist remotely.
I am available for contract and freelance work. Feel free to reach out to me on my email or social media handles.