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.

• 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

• 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)