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Overview:

We are seeking an experienced Senior Machine Learning Engineer to join our AI/ML Engineering team. You will be responsible for developing and optimizing complex data pipelines, integrating model pipelines, and building scalable AI/ML solutions, including large language models (LLMs). The ideal candidate will possess a robust background in traditional machine learning, deep learning, and significant experience with large datasets and cloud-based AI services.

Responsibilities:

+ Develop and optimize complex data pipelines, applying machine learning engineering principles to enhance efficiency and scalability.

+ Integrate and optimize data and model pipelines within production environments, diagnosing data inconsistencies and documenting assumptions.

+ Employ experimental methodologies, statistics, and machine learning concepts to create self-running AI systems for predictive modeling.

+ Collaborate with data science teams to review model-ready datasets and feature documentation, ensuring completeness and accuracy.

+ Perform data discovery and analysis of raw data sources, applying business context to meet model development needs.

+ Comfort with exploratory data exploration and tracking data lineage during inception or root cause analysis.

+ Engage with internal stakeholders to understand business processes and translate requirements into analytical approaches.

+ Write and maintain model monitoring scripts, diagnosing issues and coordinating resolutions based on alerts.

+ Serve as a domain expert in machine learning engineering on cross-functional teams for significant initiatives.

+ Stay updated with the latest advancements in AI/ML and apply them to real-world challenges.

+ Participate in special projects and additional duties as assigned.

Qualifications:

+ Undergraduate degree or equivalent experience; a graduate degree is preferred.

+ Minimum of 8 years of relevant work experience.

+ At least 3 years of hands-on experience designing ETL pipelines using AWS services (e.g., Glue, SageMaker).

+ Proficiency in programming languages, particularly Python (including PySpark, PySQL) and familiarity with machine learning libraries and frameworks.

+ Strong understanding of cloud technologies, including AWS and Azure, and experience with NoSQL databases.

+ Familiarity with Feature Store usage, LLMs, GenAI, RAG, Prompt Engineering, and Model Evaluation.

+ Experience with API design and development is a plus.

+ Solid understanding of software engineering principles, including design patterns, testing, security, and version control.

+ Knowledge of Machine Learning Development Lifecycle (MDLC) best practices and protocols.

+ Understanding of solution architecture for building end-to-end machine learning data pipelines.

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.