Principal AI/ML Engineer

Core Responsibilities

• Leads complex model development and deployment pipelines. Establishes best practices and drives innovation in data preparation and consumption.
• Integrates and optimizes existing complex data and model pipelines in a production environment. Identifies and diagnoses data inconsistencies and errors, documents assumptions, and fills 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.
• Leads engineering design for complex data pipeline designs. Proficient in developing highly efficient designs and strategies for both batch and real-time data pipelines.
• Pairs with data science teams to understand data requirements, performs data discovery for model development. Analyzes raw data sources for data quality, applies business context, and aligns with model development needs. Drives best practices and innovation in data discovery techniques.
• Engages with internal stakeholders to understand and probe business processes, develops hypotheses, structures requests, and translates requirements into an analytic approach. Participates in and influences ongoing business planning and departmental prioritization activities.
• Writes model monitoring scripts as needed. Diagnoses root causes based on model monitoring alerts and coordinates responses. Manages and resolves issues related to model monitoring alerts.
• 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 a thought partner for the enterprise.
• Participates in special projects and performs other duties as assigned.

Qualifications

• Undergraduate degree or equivalent combination of training and experience. Graduate degree preferred.
• Minimum of ten years related work experience.
• Advanced degree (Post Doctorate or PhD or Master’s in Computer Science, AI, Data Science or related field).
• At least 10+ years of industry experience.
• Deep expertise in machine learning and advanced techniques (NLP/NLU techniques), ML OPS, ML pipeline design, model deployments and model scaling.
• Familiarity with Responsible AI practices, model governance and data governance frameworks.