Job overview and responsibilities Develops and programs integrated software algorithms to structure, analyze and leverage data in systems applications. Develops and communicates statistical modeling techniques to develop and evaluate algorithms to improve product/system performance, quality, data management and accuracy. Completes programming and implements efficiencies, performs testing and debugging. Completes documentation and procedures for installation and maintenance. Applies deep learning technologies to give computers the capability to visualize, learn and respond to complex situations. Can work with large scale computing frameworks, data analysis systems and modeling environments. Design and implement key components of the Machine Learning Platform infrastructure and establish processes and best practices Work cross-functionally with data scientists, data engineers, and IT teams to design, develop, deploy, and integrate high-performance, production-grade machine learning solutions and data intensive workflows Partner with data scientists and data engineers to create and refine features from underlying data and build reproducible feature pipelines to train models and serve features in production Partner with data platform and operations teams to solve complex data ingestion, pipeline and governance problems for machine learning solutions Take ownership of production systems with a focus on delivery, continuous integration, and automation of machine learning workloads Provide technical mentorship, guidance, and quality-focused code review to data scientists and ML engineers