Building scalable and reliable ML infrastructure that supports reproducible feature engineering and machine learning model deployment.
Building pipelines that support real-time, near real-time and batch processes.
Build monitoring services to understand the data quality and model performance of complex systems.
Collaborate with the engineering and science teams to optimize existing algorithms for training and evaluation pipelines.
Independently solving moderately complex problems and writing clean, efficient, and sustainable code.
Participate in code reviews, documentation and software engineering life cycle.
