• Design, build, and operate scalable ML pipelines for various stages of the ML lifecycle • Own the end-to-end ML lifecycle, from data exploration to model validation • Continuously monitor model performance and implement automated retraining pipelines • Leverage advanced ML techniques to improve automation and predictions • Conduct in-depth data analysis to identify new opportunities for efficiency • Collaborate cross-functionally to integrate AI capabilities into Tebra’s platform • Establish best practices for model governance in healthcare environments • Lead and mentor engineers in applied ML methods and experimentation