I am a Senior AI / ML Engineer with over 8 years of experience specializing in machine learning and artificial intelligence, particularly within healthcare applications. Throughout my career, I have led the development of deep learning pipelines for medical imaging, positively impacting over 2,000 patients and significantly reducing manual review times by 35%. My expertise includes building scalable machine learning models using Python and TensorFlow, as well as designing real-time inference systems that support hospital networks.
I have a strong background in implementing MLOps frameworks, which has saved engineering teams 35 to 50 hours of manual deployment effort each month. My work involves architecting and maintaining AI services with Docker and Kubernetes, ensuring high availability and reliability. I am experienced in developing clinical NLP pipelines using transformer architectures like BERT and BioBERT, improving efficiency in medical entity recognition by 40%.
My role often requires orchestrating large-scale ETL workflows, integrating vast healthcare datasets from EHR systems such as Epic and Cerner, and deploying scalable ML infrastructure on AWS SageMaker. I have successfully led model validation and monitoring initiatives to ensure fairness and regulatory compliance, reducing false positives by 37% through automated alerting systems.
I am proficient in a wide range of programming languages including Python, Go, and JavaScript, and skilled in AI frameworks such as PyTorch, TensorFlow, and Hugging Face. My experience extends to cloud platforms like AWS, Azure ML, and Google Cloud AI Platform, as well as data engineering tools including Apache Spark and Kafka.
I am passionate about leveraging AI to improve healthcare outcomes and streamline clinical workflows. My projects include developing clinical risk prediction platforms and medical imaging classification systems that have enhanced diagnostic accuracy and operational efficiency. I am committed to continuous learning and applying cutting-edge AI technologies to solve real-world problems in healthcare.
