Welcome to my GitHub page!

• Spent over 2 years at ALS GoldSpot Discoveries, initially as a data scientist and later transitioning into an ML Engineer role. However, my responsibilities often diverged from traditional data science and ML engineering. Our main focus was on developing several SaaS products, where a more fitting title might have been MLOps Engineer. Day to day, I collaborated with my team to facilitate a fully automated ML platform for mineral exploration. This involved responding to Jira tickets assigned to me, resolving reported bugs, and implementing new features to enhance and support for the SmartTarget™ and SmartMap™ products.

• Spent over 4+ months as a Senior Data Scientist at Canadian Red Cross leveraging data-centric methods to extract insights and designing a Retrieval Augmented Generation (RAG) solution that makes it easy for staff to access clear answers and relevant links.

• Currently, working as a Machine Learning Engineer at Caylent.

• These days, my primary focus is on private repositories within the organization.

• My experience spans both analyzing data and deploying machine learning models into production, allowing me to see projects through from data analysis to operational implementation.

• Particularly interested in designing cutting-edge machine learning and AI platforms by leveraging Large Language Models (LLMs).

• Passionate about using GitHub Actions and CircleCI to create robust CI/CD pipelines, automating the deployment, testing, and monitoring of ML models in production environments.

• Also, enjoy developing machine learning pipelines that align with and advance strategic business objectives.

• Keen on exploring the intersection of image processing and machine learning, such as mineral exploration and autonomous vehicles.

• Passionate about building scalable and reliable AWS cloud architectures and currently preparing for the AWS Developer Associate Exam to further validate and enhance my DevOps skills.

• These days, I'm self-teaching how to effectively build and monitor embedded machine learning models on edge devices using the Flower framework.

Explore my some of personal projects on DockerHub and GitHub Packages

• Emotion Detection App: A Streamlit application that predicts facial emotions from uploaded images. Up and running on Railway

• Icebreaker App: The app finds the person on LinkedIn and provides a short summary about that person. Up and running on Render

• TodoList App: Todo List App is a FullStack Application built using FastAPI and SQLAlchemy. Up and running on Render and Railway

• PDF Bundle: PDF Bundle extracts text from PDFs in AWS S3, splits it, stores vector embeddings in Pinecone, and uses query vector embeddings based on cosine similarities for efficient search and retrieval. Up and running on Railway.

• Heart Attack App: Two-year Survival Predictor predicts patient survival rates following a heart attack. Up and running on Render

Explore my published research on Inspire-HEP and Google-Scholar

• 📫 Feel free to connect with me