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.
Skills Required
- 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
- 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
Vanguard Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Vanguard and has not been reviewed or approved by Vanguard.
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Retirement Support — Retirement support appears unusually strong through a 401(k) design that includes a match plus an additional employer contribution, which can materially lift long-term total rewards. HSA seeding and an enhanced employer match further strengthen the savings-and-benefits value of the package.
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Wellbeing & Lifestyle Benefits — Wellbeing and lifestyle support is reinforced by a sizable annual FlexFund stipend that can be applied across many day-to-day categories such as fitness, childcare, and other personal expenses. On-site or virtual clinics and fitness options add practical health and wellness convenience.
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Affordable Benefits — Healthcare and related benefits are positioned as comparatively affordable via heavily subsidized medical plans and broad coverage options. This affordability can offset moderate base pay for employees who place higher value on out-of-pocket cost reductions.
Vanguard Insights
What We Do
We are a community of 30 million who think – and feel – differently about investing. Together, we’re changing the way the world invests. Since our founding in 1975, helping our investors achieve their goals is our sole reason for existence. With no other parties to answer to and therefore no conflicting loyalties, we make every decision—like keeping investing costs as low as possible—with only your needs in mind. Vanguard is one of the world's largest investment companies, offering a large selection of high-quality low-cost mutual funds, ETFs, advice, and related services. Individual and institutional investors, financial professionals, and plan sponsors can benefit from the size, stability, and experience Vanguard offers. As of April 30, 2019, we managed more than $5.6 trillion in global assets. In addition, we have 189 funds in the United States and 225 funds in global markets. For Commenting Guidelines & Important information, visit here: http://vanguard.com/linkedin Vanguard Marketing Corporation, Distributor.
