Lead Machine Learning Engineer

Capital One Capital One · Banking · Chicago, IL +1

Lead Machine Learning Engineer at Capital One, focused on architecting and productionizing intelligent systems for Capital One Travel's luxury market. The role involves designing, building, and delivering ML models and components, informing ML infrastructure decisions, writing and testing application code, automating tests and deployment, and leveraging cloud-based architectures to deliver optimized ML models at scale. Responsibilities include retraining, maintaining, and monitoring models in production, constructing data pipelines, and ensuring adherence to CI/CD, Responsible AI, and Explainable AI best practices.

What you'd actually do

  1. Design, build, and/or deliver ML models and components that solve real-world business problems, while working in collaboration with the Product and Data Science teams
  2. Inform your ML infrastructure decisions using your understanding of ML modeling techniques and issues, including choice of model, data, and feature selection, model training, hyperparameter tuning, dimensionality, bias/variance, and validation)
  3. Solve complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment
  4. 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
  5. Retrain, maintain, and monitor models in production

Skills

Required

  • Bachelor's Degree
  • 6 years of experience designing and building data-intensive solutions using distributed computing
  • 4 years of experience programming with Python, Scala, or Java
  • 2 years of experience building, scaling, and optimizing ML systems

Nice to have

  • Master's or Doctoral Degree in computer science, electrical engineering, mathematics, or a similar field
  • 3+ years of experience building production-ready data pipelines that feed ML models
  • 3+ years of on-the-job experience with an industry recognized ML 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 ML models
  • 2+ years of people leader experience
  • 1+ years of experience leading teams developing ML solutions using industry best practices, patterns, and automation
  • Experience developing and deploying ML solutions in a public cloud such as AWS, Azure, or Google Cloud Platform
  • Experience designing, implementing, and scaling complex data pipelines for ML models and evaluating their performance
  • ML industry impact through conference presentations, papers, blog posts, open source contributions, or patents
  • Experience leveraging interactive AI tooling to accelerate productivity, utilizing capabilities beyond basic code completion

What the JD emphasized

  • productionizing machine learning applications and systems at scale
  • architect the intelligent systems
  • transform complex data into bespoke, anticipatory experiences
  • redefine the gold standard of travel through innovation
  • designing and building data-intensive solutions using distributed computing
  • building, scaling, and optimizing ML systems
  • building production-ready data pipelines that feed ML models
  • developing performant, resilient, and maintainable code
  • data gathering and preparation for ML models
  • leading teams developing ML solutions using industry best practices, patterns, and automation
  • designing, implementing, and scaling complex data pipelines for ML models and evaluating their performance

Other signals

  • productionizing machine learning applications and systems at scale
  • architect the intelligent systems that power Capital One Travel's vision
  • transform complex data into bespoke, anticipatory experiences
  • redefine the gold standard of travel through innovation