Lead Machine Learning Engineer

2 weeks ago

Annapolis, United States Capital One Full time

As a Lead Machine Learning Engineer at Capital One, you will be a vital member of an Agile team focused on scaling machine learning applications for real-world business challenges. You will engage in the detailed technical design, development, and deployment of machine learning systems using advanced technology platforms. Your responsibilities will include architectural design, coding for models and applications, and ensuring high availability and performance of our machine learning solutions. This is your opportunity to continuously learn and implement the latest innovations and best practices in ML engineering.

Key Responsibilities:

  • Play a multi-disciplinary role that includes elements of Operations, Modeling, and Data Engineering.

  • Collaborate with Product and Data Science teams to design and implement ML models and components that address real-world problems.

  • Make informed infrastructure decisions based on an understanding of ML techniques, model selection, data management, and feature selection.

  • Tackle complex problems by writing efficient application code, developing ML models, and automating both tests and deployment processes.

  • Work within a cross-functional Agile team to enhance software that supports cutting-edge big data and ML applications.

  • Oversee the retraining, maintenance, and monitoring of models in production.

  • Utilize cloud-based technologies to deliver scalable ML models.

  • Establish optimized data pipelines that effectively feed ML models.

  • Adopt continuous integration and continuous deployment best practices to ensure successful deployment of ML models and application code.

  • Ensure that all code is well-managed to mitigate vulnerabilities and that models comply with best practices in Responsible and Explainable AI.

  • Use programming languages such as Python, Scala, or Java.

Basic Qualifications:

  • Bachelor's degree
  • At least 4 years of programming experience with Python, Scala, or Java (Internship experience excluded)
  • Minimum of 3 years designing and building data-intensive solutions using distributed computing
  • At least 2 years of hands-on experience using recognized ML frameworks (e.g., scikit-learn, PyTorch, Dask, Spark, TensorFlow)
  • At least 1 year in productionizing, monitoring, and maintaining machine learning models

Preferred Qualifications:

  • 1+ years of experience in building and optimizing ML systems
  • 1+ years of data preparation experience for ML models
  • 2+ years of experience in developing resilient and maintainable code
  • Experience deploying ML solutions in public cloud environments such as AWS, Azure, or Google Cloud Platform
  • Master's or doctoral degree in computer science, electrical engineering, mathematics, or a related field
  • 3+ years of experience with distributed file systems or multi-node database paradigms
  • Contributions to open-source ML software
  • Authored or co-authored a research paper on ML techniques, models, or proofs of concept
  • 3+ years of experience in building production-ready data pipelines for machine learning
  • Experience in designing and scaling complex data pipelines for ML models while evaluating their performance

This position is located at Center 1, 19052, McLean, Virginia.

Capital One is committed to diversity and inclusion in the workplace. We welcome qualified applicants without regard to sex, race, color, age, national origin, religion, disability, or any other legally protected status.

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