I am a full-stack Machine Learning Engineer experienced in developing production-scale ML algorithms to solve business problems at large internet-based companies. I have contributed to the entire machine learning product development lifecycle from conception to productionization. My skills include: - Model Prototyping and Evaluation (Python, Tensorflow, Keras, Pytorch, Scikit-Learn Suite) - Model Deployment on Engineering Infrastructure (Flask, REST APIs, Docker) - Building Data Pipelines and Analytics (PySpark, Apache Airflow, SQL, Hadoop Stack) - Problem scoping, roadmapping and stakeholder communications I have a strong foundation in Machine Learning Research from my graduate studies at Carnegie Mellon University where I developed state-of-the-art algorithms in Deep Learning, Computer Vision, Reinforcement Learning and Natural Language Processing and have had the opportunity to apply ideas from academic research in an industry environment.