Senior Lead Machine Learning Engineer

• Design, build, and/or deliver machine learning models and components solving real-world business problems
• Collaborate with Product and Data Science teams
• Make ML infrastructure decisions involving model choice, data and feature selection, training, tuning, dimensionality, bias/variance, and validation
• Write and test application code, develop and validate ML models, and automate tests and deployment
• Collaborate on a cross-functional Agile team developing big data and ML applications
• Retrain, maintain, and monitor production models
• Build or leverage cloud-based architectures, technologies, and platforms to deliver optimized ML models at scale
• Construct optimized data pipelines feeding ML models
• Apply continuous integration and continuous deployment practices, test automation, and monitoring
• Manage code to reduce vulnerabilities and govern models from a risk perspective
• Apply Responsible and Explainable AI best practices
• Use Python, Scala, or Java

• Bachelor's Degree
• At least 8 years of experience designing and building data-intensive solutions using distributed computing; internship experience does not apply
• At least 4 years of programming experience 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:
  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 Tensor Flow
• 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 feeding ML models
• Ability to communicate complex technical concepts clearly to varied audiences
• Experience leveraging interactive AI tooling beyond basic code completion
• Capital One will consider sponsoring a new qualified applicant for employment authorization

Demonstrates expertise in designing and building machine learning models and data-intensive solutions, with a strong focus on cloud-based architectures and continuous integration practices. Proven ability to lead teams and communicate complex technical concepts effectively.

• Machine Learning Model Development
• Python Programming
• Cloud-Based Architecture (AWS, Azure, Google Cloud)
• Data Pipeline Construction
• Team Leadership in ML Solutions

• Machine Learning
• Data Preparation
• Model Training and Tuning
• Continuous Integration
• Continuous Deployment
• Distributed Computing
• ML Frameworks (scikit-learn, PyTorch, Tensor Flow)
• Application Code Development
• Automated Testing
• Risk Management

• Clear Communication
• Collaboration
• Team Management

• Bachelor's Degree
• Master's or Doctoral Degree (Preferred)

• Responsible AI
• Explainable AI
• ML Infrastructure
• Production Models
• Data-Intensive Solutions

• Python
• Scala
• Java
• Big Data Technologies
• Agile Methodologies