Senior Lead Machine Learning Engineer

1 day ago

Washington, Washington, D.C., United States Capital One Full time

About the Role

We are seeking a highly skilled Senior Lead Machine Learning Engineer to join our team at Capital One. As a key member of our Agile team, you will be responsible for designing, building, and deploying machine learning applications and systems at scale.

Key Responsibilities

  • Design and develop machine learning models and components that solve real-world business problems.
  • Collaborate with Product and Data Science teams to inform ML infrastructure decisions.
  • Solve complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment.
  • Collaborate as part of a cross-functional Agile team to create and enhance software that enables state-of-the-art big data and ML applications.
  • Retrain, maintain, and monitor models in production.
  • Leverage or build cloud-based architectures, technologies, and/or platforms to deliver optimized ML models at scale.
  • Construct optimized data pipelines to feed ML models.
  • Leverage continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code.
  • Ensure all code is well-managed to reduce vulnerabilities, models are well-governed from a risk perspective, and the ML follows best practices in Responsible and Explainable AI.

About the Team

In the Enterprise Data Tech Organization, customer experience is at the forefront of what we do. This team builds functional, always on scalable data ecosystems working alongside some of the savviest Data techies in the industry, enabling products and solutions to enhance customer experience and drive up satisfaction levels.

Basic Qualifications

  • Bachelor's degree
  • At least 8 years of experience designing and building data-intensive solutions using distributed computing
  • At least 4 years of experience programming with Python, Scala, or Java
  • At least 3 years of experience building, scaling, and optimizing ML systems
  • At least 2 years of experience leading teams developing ML solutions

Preferred Qualifications

  • Master's or doctoral degree in computer science, electrical engineering, mathematics, or a similar field
  • Experience developing and deploying ML solutions in a public cloud such as AWS, Azure, or Google Cloud Platform
  • 4+ years of on-the-job experience with an industry recognized ML framework such as scikit-learn, PyTorch, Dask, Spark, or TensorFlow
  • 3+ years of experience developing performant, resilient, and maintainable code
  • 3+ years of experience with data gathering and preparation for ML models
  • 3+ years of people management experience
  • ML industry impact through conference presentations, papers, blog posts, open source contributions, or patents
  • 3+ years of experience building production-ready data pipelines that feed ML models
  • Ability to communicate complex technical concepts clearly to a variety of audiences

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