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Job Description

Capital One seeks a Machine Learning Engineer focused on AI Foundations to productionize ML applications at scale, collaborating with cross-functional teams on model design, deployment, monitoring, and responsible AI practices.

Responsibilities

  • Design, develop, and deliver ML models and components that address real business needs, partnering with Product and Data Science teams.
  • Guide ML infrastructure decisions through solid modeling knowledge, including model selection, data and feature choices, training, hyperparameter tuning, dimensionality, bias/variance management, and validation strategies.
  • Tackle complex problems by writing robust application code, building and validating ML models, and automating tests and deployment processes.
  • Collaborate within a cross-functional Agile team to create and enhance software supporting state of the art big data and ML applications.
  • Retrain, monitor, and maintain models in production environments.
  • Leverage cloud-based architectures, technologies, and platforms to deliver optimized ML models at scale.
  • Construct optimized data pipelines to feed ML models efficiently.
  • Apply continuous integration and continuous deployment practices, including test automation and monitoring, to ensure successful deployment of ML models and application code.
  • Ensure code quality, governance, and risk management, and uphold responsible and explainable AI practices across models.
  • Proficiency with programming languages such as Python, Scala, or Java.

Requirements

  • Bachelor’s Degree.
  • Minimum of two years of experience designing and building data-intensive solutions using distributed computing (internship experience not counted).
  • Minimum of two years programming in Python, Scala, or Java.
  • At least one year of machine learning experience with an industry recognized framework (scikit-learn, PyTorch, Dask, Spark, or TensorFlow).

Technologies

  • Python
  • Scala
  • Java
  • scikit-learn
  • PyTorch
  • Dask
  • Spark
  • TensorFlow
  • AWS
  • Azure
  • Google Cloud Platform

Benefits

  • Health, financial and other benefits that support total well-being.
  • Performance-based incentive compensation, which may include cash bonuses and/or long term incentives (LTI).

Location

McLean, VA onsite

Compensation

USD 135,600 - 154,800 per year

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