Sreeram Raghammudi

About Sreeram Raghammudi

Machine Learning Engineer focused on NLP, multimodal AI, and applied deep learning systems, with growing specialization in machine learning for finance and quantitative research. Currently pursuing an MS in Computer Science (Machine Learning) at Columbia University. I build and deploy end-to-end AI pipelines including LLM applications, document intelligence systems, OCR and vision-language models, and scalable backend services used in production environments processing high-volume data.My work spans both engineering and research across text, vision, multimodal, and financial time-series domains. I am currently developing multimodal transformer systems for historical document recovery using spectral imaging and graph-based analysis. In parallel, I conduct ML-for-finance research on market connectedness, crisis spillovers, and deep learning for financial forecasting, leveraging VAR models, cross-quantilograms, CNN-LSTMs, and feature selection pipelines for multi-market prediction.I focus on building models that are not only accurate, but also efficient, interpretable, and deployable under real-world constraints.I’m interested in applied AI and quant-oriented roles where strong modeling meets real-world systems,building scalable ML solutions, optimizing model efficiency under hardware constraints, and solving complex problems across NLP, vision, multimodal data, and financial markets.

Experience

1. Ai Ml and Backend Development Intern

   Odex

   Jan 2025 — Present · Dubai, AE

Education

• DELHI PUBLIC SCHOOL KAMPTEE ROAD NAGPUR

  Class 10th

  2009 — 2019

• Columbia University

  Master of Science - MS , Computer Science (Machine Learning Track)

• Birla Institute of Technology and Science, Pilani

  Bachelor of Engineering - BE, Computer Science

  2021 — 2025