Facilitates the implementation of processes for machine learning (ML) model
productionization to managers. Implements organizational standards around
machine learning model readiness for deployment. Promotes organizational
strategy around the automation of machine learning workflows. Promotes
organizational strategy around trained model/system alignment with design
criteria. Implements improvements to organizational processes for the
identification and evaluation of potential data quality, security, and/or
privacy issues and their impacts on modeling. Facilitates organizational
troubleshooting and debugging support processes to address issues in machine
learning infrastructure and workflow and create robust solutions. Alleviates the
impact of obstacles to cross-functional collaboration efforts with multiple
stakeholders to make, adopt and communicate technical decisions and shape the
development and delivery of software. Implements organizational processes for
the development, refinement, and maintenance of tools, platforms, environments,
and services for internal use.
Implements improvements to organizational
processes for the development of efficient, bug-free code from scratch. Executes
organizational strategy to maintain team awareness of current developments in
the machine learning field and integration of this knowledge into model
development.
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