As a Principal Machine Learning Engineer at Vanguard, you will collaborate with a highly innovative and vibrant team of Data Scientists, Machine Learning Engineers, Cloud Engineers, and Data Engineers to develop the next generation of AI/ML-enabled financial fraud and financial crimes prevention solutions. You will lead the development of machine learning algorithms and pipelines to structure, analyze, and leverage data in a production environment.  You will partner with business stakeholders to prioritize innovation ideas and work with other Engineers and Data Scientists to develop and deliver breakthrough solutions. Additionally, you will mentor and develop junior machine learning engineers, demonstrating expertise in machine learning models, deployment architecture, and advanced techniques.

Core Responsibilities:

Lead engineering design and deployment of complex data and model pipelines. Establish best practices and drive innovation in end-to-end data and model pipeline deployment and automation technologies. Expert-level knowledge in SDLC and related tools and processes. Proficient in developing highly efficient designs and strategies for both batch and real-time data pipelines.

Integrate and optimize existing data and model pipelines. Identify and diagnose data inconsistencies and errors, document assumptions, and fill data gaps. Apply expert knowledge of experimental methodologies, statistics, optimization, probability theory, and machine learning concepts to create self-running AI systems for automating data science models.

Partner with data science teams to understand data requirements and perform data discovery for model development. Perform detailed analysis of raw data sources for data quality, apply business context, and model development needs. Drive best practices and innovation in data discovery techniques. Write model monitoring scripts as needed. Diagnose root causes based on model monitoring alerts and triage issues. Coordinate and plan responses to model monitoring alerts and resolve issues.

Demonstrate strategic thinking and apply expertise in cloud-based architectures, technologies (including GenAI), and platforms to deliver optimized ML models at scale.

Drive engineering innovation in the labs through effective collaboration with data scientists, technologists, and business stakeholders. Drive roadmap/strategy discussions with product owners and business partners as a trusted advisor for engineering/technology.

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. 

Qualifications:

MS in Computer Science, Statistics, Machine Learning, Data Science, Electrical Engineering, or related field.

Minimum of ten years related work experience, with 5+ years of experience in deploying and maintaining AI/ML related projects.

Advanced programming skills, particularly in languages like Python. Proficiency in using AWS machine learning services, such as Sagemaker, for model pipeline development, training, and deployment. Proven ability to develop and deploy machine learning models with robust data architectures.

Proficiency in AWS Cloud Formation for infrastructure as code. Experience with CI/CD practices for both machine learning and data engineering workflows.

Experience with data processing technologies, such as Apache Spark, AWS Glue, and Hadoop.

Ability to convey technical concepts to diverse stakeholders and demonstrate thought leadership in engineering space. Strong technical skills on ML/AI with a proven track record.

Special Factors

Sponsorship

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.

Our commitment to diversity, equity, and inclusion

Vanguard’s commitment to diversity, equity, and inclusion (DEI) is central to our ability to deliver on our mission. We aspire to create a work environment that is inclusive, equitable, and diverse—one that enables our employees, whom we call crew, to thrive and bring their best selves to work every day on behalf of our clients.

Cultivating DEI lifts our entire organization, and everyone shares accountability for our progress—from our senior leaders who lay the foundation and set the example for inclusive behaviors to crew who are growing in their personal DEI learning experiences.

Together, we’re on a mission. We are fueled by the value of diverse voices and connected through friendships and a culture of care—for our clients, our communities, and each other.    

Vanguard’s DEI journey has no finish line. Our commitment is enduring, and we remain focused on the path ahead. To learn more about Vanguard goals and progress toward DEI, download our Diversity, Equity, and Inclusion Report.

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.