Senior Machine Learning Engineer

**Core Responsibilities** - Design, build, and maintain end-to-end machine learning pipelines from research through production deployment. - Engineer scalable training, inference, and retraining workflows using AWS SageMaker. - Develop and maintain feature engineering, feature storage, and data preparation pipelines. - Automate model deployment, testing, validation, and release processes using CI/CD practices. - Build batch, real-time, and event-driven architectures. - Implement model monitoring for performance, drift detection, data quality, and operational health. - Partner with quantitative researchers and data scientists to productionalize research models. - Manage model versioning, lineage tracking, experiment management, and reproducibility. - Optimize model performance, scalability, reliability, and cloud cost efficiency. - Establish engineering standards, testing frameworks, and governance controls for ML solutions. - Support production operations, incident response, and continuous improvement of deployed models. **Required Qualifications:** - Minimum of eight years related work experience, with at least three years of development experience. - Undergraduate degree or equivalent combination of training and experience. Graduate degree preferred. - Experience in software engineering, machine learning engineering, data engineering, or a related technical discipline. - Strong experience building and deploying machine learning solutions in production environments. - Expertise in Python and modern data science libraries (Pandas, NumPy, Scikit-Learn, PyTorch, TensorFlow, or similar). - Hands-on experience with AWS services, including SageMaker - Experience building and maintaining machine learning pipelines, feature engineering workflows, and model deployment processes. - Knowledge of MLOps practices, including CI/CD, model versioning, experiment tracking, monitoring, and automated retraining. - Strong understanding of software development lifecycle practices, testing strategies, and production support. - Ability to work effectively with researchers, data scientists, and business stakeholders to deliver business outcomes. ​ **Special Factors** **Sponsorship** Vanguard is not 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.