• Work closely with Machine Learning Engineers to understand, refine, and prioritize requirements • Design and build our model serving service with simple, powerful APIs to capture our users/clients needs • Build our core ML model lifecycle management system to provide an ML-aware release and deployment experience • Improve machine learning data quality by using & building tools to automatically detect issues • Create intelligent ML-aware real-time monitoring & observability systems • Work closely with partner teams to integrate with other ML tools to create a seamless end-to-end experience • Leverage open-source technologies like Kubeflow, Kubernetes, Spark, Docker, Airflow, Tensorflow, and PyTorch