Core Responsibilities
1. Develops complex data pipelines and implements machine learning engineering design principles for iterative ML pipeline development to drive scale and efficiency. Proficient in model development environments and coding standard methodologies to enable model deployment.
2. Integrates and optimizes existing data and model pipelines in a production environment. Identifies and diagnoses data inconsistencies and errors, documents assumptions, and forages to fill data gaps. Applies knowledge of experimental methodologies, statistics, optimization, probability theory, and machine learning concepts to create self-running artificial intelligence (AI) systems to automate predictive models. Proficient in MDLC processes and related tools and technologies.
3. Partners with data science teams to review model ready dataset document/feature documentation. Develops data model design and document and reviews for completeness with data science teams.
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 efficiency through the use of data discovery tools.
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 domain expert on multi-functional teams for large critical initiatives and contributes to the growth of the Vanguard analytic community.
8. Participates in special projects and performs other duties as assigned.
Qualifications
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7+ years' experience building machine learning pipelines.
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5+ years' experience with AWS Stack.
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3+ years of hands-on experience with designing ETL pipelines using AWS GIS.
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3+ years' experience deploying model as end points in AWS using AWS Sagemaker.
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Proficient in Python Coding and its variants (PySpark, PySQL etc..)
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Good understanding of Feature Store and its usage in gen AI technology.
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Experience with MDLC (Machine Learning Development Lifecyle) standard methodologies and protocols.
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Undergraduate degree or equivalent experience or equivalent combination of training and experience. Graduate degree preferred.
Special Factors
Sponsorship
Vanguard is offering visa sponsorship for this position.
About Vanguard
At Vanguard, we don't just have a mission—we're on a mission.
To work for the long-term financial wellbeing of our clients. To lead through product and services that transform our clients' lives. To learn and develop our skills as individuals and as a team. From Malvern to Melbourne, our mission drives us forward and inspires us to be our best.
How We Work
Vanguard has implemented a hybrid working model for the majority of our crew members, designed to capture the benefits of enhanced flexibility while enabling in-person learning, collaboration, and connection. We believe our mission-driven and highly collaborative culture is a critical enabler to support long-term client outcomes and enrich the employee experience.
Top Skills
What We Do
We are a community of 30 million who think – and feel – differently about investing. Together, we’re changing the way the world invests.
Since our founding in 1975, helping our investors achieve their goals is our sole reason for existence. With no other parties to answer to and therefore no conflicting loyalties, we make every decision—like keeping investing costs as low as possible—with only your needs in mind.
Vanguard is one of the world's largest investment companies, offering a large selection of high-quality low-cost mutual funds, ETFs, advice, and related services. Individual and institutional investors, financial professionals, and plan sponsors can benefit from the size, stability, and experience Vanguard offers. As of April 30, 2019, we managed more than $5.6 trillion in global assets. In addition, we have 189 funds in the United States and 225 funds in global markets.
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