Professional Machine Learning Engineer

As a certified Professional Machine Learning Engineer, I possess the expertise to build, evaluate, productionize, and optimize AI solutions by effectively utilizing Google Cloud capabilities alongside my knowledge of conventional ML approaches. I am adept at handling large, complex datasets and developing repeatable, reusable code, including designing and operationalizing generative AI solutions built upon foundational models. Throughout my work, I consistently consider responsible AI practices and collaborate closely with various teams to ensure the long-term success and adoption of AI-based applications across an organization.

My skill set is distinguished by strong programming abilities and extensive experience with data platforms and distributed data processing tools. I am proficient in model architecture, the creation of robust data and ML pipelines, the application of generative AI, and the critical interpretation of performance metrics. Furthermore, I am familiar with the foundational concepts of MLOps, application development, infrastructure management, data engineering, and data governance.

By training, retraining, deploying, scheduling, monitoring, and continuously improving models, I design and create scalable, high-performing solutions. This includes architecting low-code AI solutions using tools like BigQuery ML and AutoML, building AI solutions with ML APIs or foundational models from Model Garden, and implementing retrieval augmented generation (RAG) applications using Vertex AI Agent Builder. I am also skilled in prototyping models in Jupyter environments on Google Cloud, tracking ML experiments, and choosing appropriate hardware for training and serving, ensuring efficient and effective AI deployment.