Machine Learning Engineer

Role Summary

The Chief Data & Analytics Office (CDAO) is looking for a Machine Learning Engineer to build efficient, data-driven AI systems that advance our predictive automation capabilities.

You should be highly skilled in statistics and programming, with the ability to confidently assess, analyse, and organize large amounts of data. You should also be able to execute tests and optimize Vanguard's machine learning models and algorithms.

You will play a critical role in designing and developing machine learning algorithms and AI applications and systems for Vanguard, solve complex problems with multilayered data sets, and optimize existing machine learning libraries and frameworks. You will collaborate with data scientists, data analysts, data engineers, and data architects on production systems and applications, and identify differences in data distribution that could potentially affect model performance in real-world applications.
 

What will you be doing?

You will be a major contributor in our GenAI intake process, assessing and reviewing use cases from around the business, and play a key role in Vanguard's model governance processes.
In addition, you will:

Design, build, and productionize machine learning and GenAI solutions, ensuring they meet scalability, reliability, and performance requirements for enterprise use

Partner with data scientists to translate experimental models into robust, well‑engineered systems ready for deployment in production environments

Develop and maintain ML pipelines including feature engineering, model training, evaluation, versioning, monitoring, and automated retraining workflows

Enhance our MLOps capabilities by contributing to CI/CD pipelines, infrastructure automation, model registries, and containerized deployment frameworks

Conduct thorough model evaluation, including benchmarking, drift detection, fairness analysis, and performance optimization to ensure models behave consistently in real‑world scenarios

Collaborate with data engineers and architects to improve underlying data quality, data flows, and platform capabilities used for ML development

Perform advanced experimentation, leveraging modern ML frameworks to prototype new algorithms, assess their viability, and recommend adoption paths

Support CDAO governance processes, ensuring models comply with Vanguard’s standards for transparency, risk controls, documentation, and regulatory alignment.

Advise business teams and product owners, helping shape opportunities for automation, prediction, and GenAI enablement across the organization.

Contribute to best practices and reusable ML components, strengthening our internal libraries, frameworks, and engineering standards.

Stay current with emerging AI trends, evaluating new tools, foundation models, and methodologies to guide strategic adoption within CDAO.

What it takes

Programming: Strong proficiency in Python

Machine Learning Frameworks: TensorFlow, PyTorch, Scikit-learn

Statistics & Mathematics: Advanced knowledge of statistics, probability, and optimization

Model Development & Optimization: Building, testing, and tuning ML models and algorithms

Data Handling: Experience with large, complex datasets; SQL and data preprocessing

MLOps & Deployment: Familiarity with CI/CD, Docker, Kubernetes, and cloud platforms (AWS)

Generative AI & Model Governance: Understanding of GenAI use cases and compliance processes

Special Factors 

Vanguard is not offering sponsorship for this position

This is a hybrid position and would require you to work in the office 3 days per week (Tuesday, Wednesday & Thursday) 

Why Vanguard? 

Vanguard is a different kind of investment company. It was founded in the United States in 1975 on a simple but revolutionary idea: that an investment company should manage its funds solely in the interests of its clients. 

This is a philosophy that has helped millions of people around the world to achieve their goals with low-cost, uncomplicated investments. 

It's what we stand for: value to investors. 

Inclusion Statement

Vanguard’s continued commitment to diversity and inclusion is firmly rooted in our culture. Every decision we make to best serve our clients, crew (internally employees are referred to as crew), and communities is guided by one simple statement: “Do the right thing.”

We believe that a critical aspect of doing the right thing requires building diverse, inclusive, and highly effective teams of individuals who are as unique as the clients they serve. We empower our crew to contribute their distinct strengths to achieving Vanguard’s core purpose through our values. 

When all crew members feel valued and included, our ability to collaborate and innovate is amplified, and we are united in delivering on Vanguard's core purpose: to take a stand for all investors, to treat them fairly, and to give them the best chance for investment success.

Our commitment to equal employment opportunity 

Vanguard is an equal opportunity employer. Vanguard is committed to providing all crew members a working environment that is free from discrimination, prejudice and bias. Through this Equal Employment Opportunity (EEO) Policy, Vanguard reaffirms its commitment to equal employment opportunity for all applicants and crew members without regard to race, color, national origin or ancestry, religion, gender, sex, sexual orientation, gender identity or expression, age, disability, marital status, veteran or military status. In addition, Vanguard prohibits discrimination based on genetic information, as well as any other characteristic protected by federal, state or local law.

Applicants with disabilities may be entitled to reasonable accommodation under the Americans with Disabilities Act and certain state or local laws. A reasonable accommodation is a change in the way things are normally done which will ensure an equal employment opportunity without imposing undue hardship on Vanguard. Please inform  if you need assistance completing this application or to otherwise participate in the application process.

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.