gaberialcasey User

I am a Machine Learning Engineer with 5 years of experience in building scalable models and automating pipelines to solve real-world business challenges. My expertise lies in deploying end-to-end ML solutions using frameworks such as PyTorch, TensorFlow, and Scikit-learn, with a strong focus on Natural Language Processing (NLP), Computer Vision, and Generative AI. I have a proven ability to collaborate across teams to deliver measurable business value.

In my most recent role as a Senior Machine Learning Engineer at Guideline, I designed and deployed end-to-end ML pipelines for real-time recommendation systems, which successfully reduced churn by 17%. I developed NLP models using BERT for customer support classification, achieving an impressive 95% F1 score. Additionally, I led MLOps integration using MLflow and Docker, cutting deployment time by 40%, and mentored three junior ML engineers and data scientists.

Previously, as a Machine Learning Engineer at Instabase, I built predictive models for financial forecasting and risk classification using ensemble techniques. I automated data pipelines with Airflow, reducing manual ETL time by 60%, and implemented computer vision models (CNN) for document parsing with over 85% accuracy. My journey began as a Data Science Intern at Grammarly, where I assisted in collecting and preprocessing sales data for forecasting models.