Capital One

Senior Lead Machine Learning Engineer

Capital One

full-time

Posted on:

Location Type: Hybrid

Location: New York City • New York, Virginia • 🇺🇸 United States

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Salary

💰 $225,400 - $280,600 per year

Job Level

Senior

Tech Stack

AWSAzureCloudGoogle Cloud PlatformJavaOpen SourcePythonPyTorchScalaScikit-LearnSparkTensorflow

About the role

  • As a Capital One Machine Learning Engineer (MLE), you'll be part of an Agile team dedicated to productionizing machine learning applications and systems at scale.
  • Participate in the detailed technical design, development, and implementation of machine learning applications using existing and emerging technology platforms.
  • Focus on machine learning architectural design, develop and review model and application code, and ensure high availability and performance of our machine learning applications.
  • Continuously learn and apply the latest innovations and best practices in machine learning engineering.
  • The MLE role overlaps with many disciplines, such as Ops, Modeling, and Data Engineering.
  • Perform many ML engineering activities, including one or more of the following: 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.
  • 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).
  • Solve complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment.
  • 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.
  • Retrain, maintain, and monitor models in production.
  • Leverage or build cloud-based architectures, technologies, and/or platforms to deliver optimized ML models at scale.
  • Construct optimized data pipelines to feed ML models.
  • Leverage continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code.
  • Ensure all code is well-managed to reduce vulnerabilities, models are well-governed from a risk perspective, and the ML follows best practices in Responsible and Explainable AI.
  • Use programming languages like Python, Scala, or Java.

Requirements

  • 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 experience programming 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
  • Master's or doctoral degree in computer science, electrical engineering, mathematics, or a similar field (Preferred)
  • Experience developing and deploying ML solutions in a public cloud such as AWS, Azure, or Google Cloud Platform (Preferred)
  • 4+ years of on-the-job experience with an industry recognized ML framework such as scikit-learn, PyTorch, Dask, Spark, or TensorFlow (Preferred)
  • 3+ years of experience developing performant, resilient, and maintainable code (Preferred)
  • 3+ years of experience with data gathering and preparation for ML models (Preferred)
  • 3+ years of people management experience (Preferred)
  • ML industry impact through conference presentations, papers, blog posts, open source contributions, or patents (Preferred)
  • 3+ years of experience building production-ready data pipelines that feed ML models (Preferred)
  • Ability to communicate complex technical concepts clearly to a variety of audiences (Preferred).
Benefits
  • Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being.

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard skills
machine learningPythonScalaJavaML frameworksscikit-learnPyTorchDaskSparkTensorFlow
Soft skills
communicationteam leadershipproblem solvingcollaborationtechnical design
Certifications
Bachelor's degreeMaster's degreeDoctoral degree
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