Senior Machine Learning Engineer

Senior Machine Learning Engineer

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locations

Malvern, PA

time type

Full time

posted on

Posted 16 Days Ago

time left to apply

End Date: August 16, 2026 (6 hours left to apply)

job requisition id

179776

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.

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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.