Location:Toronto, Ontario
Remote: Yes
Willing to relocate: Yes
Frameworks & Technologies: NumPy, Pandas, Scikit-Learn, PyTorch, TensorFlow, Keras, Google GenAI, LangChain, Hugging Face, PySpark, Jupyter Notebook, Linux, Git, React, TypeScript, R Language, tidyverse, SQL, AWS, GCP.
ML & DL Techniques: Neural Network, RAG, Multi-Agents, Transformers, Principal Component Analysis, KNN/Logistic/Multinomial Regression, Random Forest, AdaBoost, Support Vector Machine, Clustering.
Github: https://github.com/billy-enrizky
Portfolio: https://billy-enrizky.github.io/portfolio/
CV: https://drive.google.com/file/d/1tE7GedAZgk3wVBJ7eNjIMVJBwyC...
Email: billy.suharno@gmail.com
About me: a results‑driven machine learning developer professional graduating May 2026, with deep expertise in building and deploying scalable AI solutions. Proficient in NumPy, Pandas, Scikit‑Learn, PyTorch, TensorFlow, Keras, LangChain, Hugging Face, PySpark, AWS, GCP, SQL and React/TypeScript. As a Machine Learning Developer at IBM, he architected an end‑to‑end, multi‑agent Text‑to‑SQL pipeline achieving 93% accuracy and delivered a multimodal RAG system with 97% relevancy, securing over $300 K in contracts. At Toronto General Hospital (T‑CAIREM Award), he engineered a 122 GB pathology slide pipeline, boosting model accuracy from 56% to 83% and achieving 91% on a multimodal fusion model. During a Summer Research Award, he processed 60 high‑resolution videos using OpenCV and MediaPipe. At Sanofi, he built an ETL pipeline handling billions of records and implemented a two‑click Snowflake/Streamlit workflow, cutting manual cycles from days to seconds. A collaborative leader, he consistently enhances team productivity through agile methodologies and data‑driven innovation.