Machine Learning Engineering

1. Leads complex model development and deployment pipelines. Establishes best practices and drives innovation in data preparation and consumption. Expert in end-to-end data and model pipeline deployment and automation technologies.
2. Integrates and optimizes existing complex data and model pipelines in a production environment. Identifies and diagnoses data inconsistencies and errors, documents assumptions, and forages to fill data gaps. Applies expert knowledge of experimental methodologies, statistics, optimization, probability theory, and machine learning concepts to create self-running artificial intelligence (AI) systems to automate predictive models. Expert level knowledge in SDLC and related tools and processes. Serves as a thought partner for Machine Learning Operations team.
3. Leads engineering design for complex data pipeline designs. Proficient in developing highly efficient designs and strategy for both batch and real-time data pipelines.
4. Partners with data science teams to understand data requirements, performs data discovery for model development. Performs detailed analysis of raw data sources for data quality, applies business context, and model development needs. Drives best practices and innovation in data discovery techniques.
5. Engages with internal stakeholders to understand and probe business processes and develop hypotheses. Brings structure to requests and translates requirements into an analytic approach. Participates in and influences ongoing business planning and departmental prioritization activities.
6. Writes model monitoring scripts as needed. Diagnoses root causes based on model monitoring alerts and triages issues. Coordinates and plans response to model monitoring alerts and resolves issues.
7. Serves as a machine learning engineering subject matter expert on cross functional teams for large strategic initiatives and contributes to the growth of the Vanguard analytic community. Serves as data and Machine Learning engineering thought partner for the enterprise.
8. Participates in special projects and performs other duties as assigned.
9. Designs advanced analytical protocols for mining large-scale datasets to uncover predictive patterns and optimize strategic initiatives.
10. Applies big data modeling techniques across domains such as market intelligence, advertising, and scientific research to inform critical business decisions.
11. Explores cutting-edge AI and data science frameworks to develop scalable, next-gen machine learning architectures.