Machine Learning Engineer
Geelong, Victoria, Australia
๐ Led the integration, containerization, and deployment of generative AI models like GANBLR and MedGAN within the Katabatic project, an open-source framework for synthetic tabular data generation.๐ง Technologies: Python, Tensorflow, Docker, MLFlow, API Development, MLOps, and evaluation metrics like Kolmogorov-Smirnov tests and Membership Inference Attacks.โจ Key Achievements:โข Resolved complex dependency conflicts to ensure seamless execution of models across environments. โข Developed a standardized API template for model integration, improving efficiency in deploying models like GANBLR and MEG. โข Designed comprehensive Docker environments for local and cloud deployment, enabling scalability and portability of the framework. ๐ Overcame challenges in aligning diverse model architectures and dependencies, while mentoring teammates in model setup, API design, and MLOps best practices.๐ ๏ธ Role: Led the model integration, containerization (Docker), and API development, ensuring robust, scalable solutions for the teamโs synthetic data generation pipeline.๐๏ธโ๐จ๏ธ Impact: Delivered scalable, production-ready AI models, enhanced collaboration, and contributed high-quality, reusable code to the open-source AI community.