Senior Machine Learning Engineer

Vanguard Group, Inc.

$120K — $150K *
Information Technology
8 - 10 years of experience
Job Overview by Ladders

Qualifications

  • 8+ years of relevant experience, including 3+ years in development roles.
  • Bachelor's degree required; graduate degree preferred.
  • Experience in software, machine learning, or data engineering.
  • Proven track record of deploying machine learning solutions in production.
  • Proficiency in Python and data science libraries such as Pandas and TensorFlow.
  • Hands-on experience with AWS, particularly SageMaker.
  • Strong understanding of MLOps practices and software development lifecycle.

Responsibilities

  • Design, build, and maintain machine learning pipelines from research to production.
  • Engineer scalable training and deployment workflows using AWS SageMaker.
  • Develop feature engineering and data preparation pipelines.
  • Automate deployment, testing, and validation processes using CI/CD.
  • Build architectures for batch, real-time, and event-driven processing.
  • Implement monitoring for model performance and data quality.
  • Collaborate with researchers to productionalize machine learning models.
  • Manage model versioning and ensure reproducibility of experiments.
  • Optimize performance and cloud cost-efficiency of models.
  • Support production operations and continuous improvement of deployed models.

Benefits

  • Comprehensive health plans and wellness programs.
  • Retirement savings options with company match.
  • Dynamic work environment focused on innovation.
  • Salary and professional development opportunities.
  • Work-life balance initiatives and flexible scheduling.
Full Job Description

CoreResponsibilities

  • 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-drivenarchitectures.
  • Implement model monitoring for performance, drift detection, data quality, and operational health.
  • Partner with quantitative researchers and data scientists toproductionalizeresearch 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 ofMLOpspractices, 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.

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