Sr Lead Machine Learning Engineer

Capital One is seeking a Sr Lead Machine Learning Engineer to join an Agile team focused on productionizing machine learning applications and systems at scale. The role involves designing, developing, and deploying ML models and infrastructure for real-time decisioning across customers’ credit journeys.

Responsibilities

• Design, build, and/or deliver machine learning models and components to address real-world business needs in collaboration with Product and Data Science teams.
• Drive ML infrastructure decisions based on ML modeling fundamentals, including model selection, data and feature selection, model training, hyperparameter tuning, dimensionality, bias/variance, and validation.
• Solve complex problems through application development and testing, building and validating ML models, and automating tests and deployment.
• Collaborate within a cross-functional Agile team to create and enhance software supporting advanced big data and ML applications.
• Retrain, maintain, and monitor models in production to support continued performance and reliability.
• Leverage and/or build cloud-based architectures, technologies, and platforms to deliver optimized ML models at scale.
• Construct optimized data pipelines that provide inputs for ML models.
• Apply continuous integration and continuous deployment best practices, including test automation and monitoring, to support successful deployment of ML models and application code.
• Ensure code is managed to reduce vulnerabilities, keep models well-governed from a risk perspective, and apply Responsible and Explainable AI best practices.
• Use programming languages such as Python, Scala, or Java.

Requirements

• Bachelor’s Degree.
• 8+ years of experience designing and building data-intensive solutions using distributed computing (internship experience does not apply).
• 4+ years of experience programming with Python, Scala, or Java.
• 3+ years building, scaling, and optimizing ML systems.
• 2+ years leading teams developing ML solutions.

Technologies

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

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 including 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.
• Experience leveraging interactive AI tooling to accelerate productivity using capabilities beyond basic code completion.

Location and Salary

McLean, VA (onsite). Salary range: USD 229,900 - 262,400 per year.

Benefits

• Eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI).
• Comprehensive, competitive, and inclusive set of health, financial and other benefits.