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Lead Machine Learning Engineer

1 month ago

Chicago, Illinois, United States Capital One Full time
Job Summary

Capital One is seeking a highly skilled Lead Machine Learning Engineer to join our team. As a key member of our Agile team, you will be responsible for designing, building, and implementing machine learning applications using emerging technology platforms. You will work closely with our Product and Data Science teams to develop and deploy scalable and efficient machine learning solutions.

Key Responsibilities
  • Design and develop machine learning models and components that solve real-world business problems.
  • Collaborate with cross-functional teams to create and enhance software that enables state-of-the-art big data and machine learning applications.
  • Retrain, maintain, and monitor models in production.
  • Leverage cloud-based architectures, technologies, and platforms to deliver optimized machine learning models at scale.
  • Construct optimized data pipelines to feed machine learning models.
  • Ensure all code is well-managed to reduce vulnerabilities, models are well-governed from a risk perspective, and the machine learning follows best practices in Responsible and Explainable AI.
Requirements
  • Bachelor's degree in Computer Science, Electrical Engineering, Mathematics, or a related field.
  • At least 6 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 2 years of experience building, scaling, and optimizing machine learning systems.
Preferred Qualifications
  • Master's or doctoral degree in Computer Science, Electrical Engineering, Mathematics, or a related field.
  • 3+ years of experience building production-ready data pipelines that feed machine learning models.
  • 3+ years of on-the-job experience with an industry-recognized machine learning framework such as scikit-learn, PyTorch, Dask, Spark, or TensorFlow.
  • 2+ years of experience developing performant, resilient, and maintainable code.
  • 2+ years of experience with data gathering and preparation for machine learning models.
  • 2+ years of people leader experience.
  • 1+ years of experience leading teams developing machine learning solutions using industry best practices, patterns, and automation.
  • Experience developing and deploying machine learning solutions in a public cloud such as AWS, Azure, or Google Cloud Platform.
  • Experience designing, implementing, and scaling complex data pipelines for machine learning models and evaluating their performance.
  • Machine learning industry impact through conference presentations, papers, blog posts, open source contributions, or patents.