Implementing scalable machine learning pipelines remains challenging despite advancements in deep learning, with issues such as model iteration, work reproducibility, and retention of institutional knowledge posing significant obstacles. Gideon Mendels, Co-founder and CEO of Comet, plans to address these challenges in an upcoming webinar, drawing from his extensive experience in machine learning research and development at Columbia University, Google, and Comet. The webinar aims to provide insights into enhancing machine learning development through emerging software tools and algorithmic improvements, focusing on reproducibility, automated hyperparameter optimization, and increasing team collaboration and model visibility.