Core Responsibilities + Design, develop, and optimize complex data pipelines using machine learning engineering best practices to ensure scalability, efficiency, and reliability. + Develop and implement robust MLOps pipeline to support the deployment, monitoring, and lifecycle management of AI/ML models in production environments. + Integrate and maintain data and model pipelines, proactively diagnosing data quality issues and documenting assumptions. + Collaborate closely with data scientists to validate model-ready datasets and ensure thorough, accurate feature documentation. + Conduct exploratory data analysis and discovery on raw data sources, incorporating business context to support model development. + Track data lineage and perform root cause analysis during early-stage exploration or issue resolution. + Partner with internal stakeholders to understand business processes and translate them into scalable analytical solutions. + Develop and maintain model monitoring scripts, investigate alerts, and coordinate timely resolutions. + Act as a subject matter expert in machine learning engineering on cross-functional teams, contributing to high-impact initiatives. + Stay current with advancements in AI/ML and evaluate their applicability to business challenges. Qualifications: + Bachelor’s degree in a relevant field required; Master’s degree preferred. + 6+ years of relevant experience in data engineering or machine learning engineering. + Minimum 3 years of hands-on experience building ETL pipelines using AWS services + Proven experience developing and implementing MLOps pipeline for deploying, monitoring, and managing AI/ML models in production. + Proficient in Python and familiar with key machine learning frameworks and libraries. + Strong understanding of cloud technologies and AI/ML platforms like AWS SageMaker. + Solid grasp of software engineering principles, including design patterns, testing, security, and version control. + Knowledge of the Machine Learning Development Lifecycle (MDLC) and best practices. + Experience designing and implementing end-to-end machine learning pipelines and solution architectures. 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.