Capital One

Lead Machine Learning Engineer

Capital One

full-time

Posted on:

Location Type: Office

Location: San Francisco • California, New York, Virginia • 🇺🇸 United States

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Salary

💰 $197,300 - $225,100 per year

Job Level

Senior

Tech Stack

AWSAzureCloudGoogle Cloud PlatformJavaPythonPyTorchScalaScikit-LearnSparkTensorflow

About the role

  • 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 ML applications
  • Design, build, and/or deliver ML models and components that solve real-world business problems, collaborating with Product and Data Science teams
  • Inform ML infrastructure decisions using understanding of ML modeling techniques and issues
  • 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

Requirements

  • Bachelor’s Degree
  • At least 6 years of experience designing and building data-intensive solutions using distributed computing
  • At least 4 years of experience programming with Python, Scala, or Java
  • At least 2 years of experience building, scaling, and optimizing ML systems
  • Master’s or Doctoral Degree in computer science, electrical engineering, mathematics, or a similar field preferred
  • 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 preferred
  • 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 preferred
  • 1+ years of experience leading teams developing ML solutions using industry best practices, patterns, and automation preferred
  • Experience developing and deploying ML solutions in a public cloud such as AWS, Azure, or Google Cloud Platform preferred
  • Experience designing, implementing, and scaling complex data pipelines for ML models and evaluating their performance preferred
Benefits
  • 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 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
collaborationproblem-solvingleadershipcommunicationAgile methodology
Certifications
Bachelor’s DegreeMaster’s DegreeDoctoral Degree