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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.