Machine Learning Engineer 5 (Senior Manager, IC)

Capital One is seeking a senior-level Machine Learning Engineer to design, build, and scale machine learning models and platforms. This onsite role in New York, NY combines hands-on ML engineering, production deployment, and ongoing model monitoring at scale. You will collaborate with Product and Data Science teams to help deliver real-world solutions, from model development through resilient operations.

Compensation: USD 250,800 - 286,200 per year (New York, NY). This position is eligible for performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Capital One also offers a comprehensive, competitive, and inclusive set of health, financial and other benefits to support total well-being.

What you’ll do

• Design, build, and/or deliver ML models and components that address real business problems in collaboration with Product and Data Science teams.
• Build and scale massive multi-tenant platforms that support large footprint training and/or serving at scale.
• Apply ML modeling expertise to influence infrastructure decisions, including model choice, data and feature selection, training approaches, hyperparameter tuning, dimensionality choices, bias/variance tradeoffs, and validation.
• Solve complex problems through application code, ML model development, validation, and automated testing and deployment.
• Work in a cross-functional Agile environment to create and enhance software enabling big data and ML applications.
• Retrain, maintain, and monitor models in production.
• Use or build cloud-based architectures, technologies, and/or platforms to deliver optimized ML models at scale.
• Construct optimized data pipelines to feed ML models.
• Use CI/CD best practices, including test automation and monitoring, to support successful deployment of ML models and application code.
• Maintain well-managed code to reduce vulnerabilities, support risk-governed model practices, and follow Responsible and Explainable AI best practices.
• Develop using Python, Scala, or Java.

What you’ll need

• Bachelor’s Degree or higher in Computer Science, Machine Learning, or a related quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Engineering).
• At least 6 years of experience programming with Python, Java, Golang, or C++.
• At least 6 years of ML experience using PyTorch or Tensorflow and libraries including Pandas, NumPy, Scikit-learn.
• At least 6 years using and operating large-scale distributed systems such as Spark and Ray to prepare AI/ML data.
• At least 4 years deploying and operating ML solutions in production, operating production services in AWS, GCP, or Azure, and using Kubernetes for large-scale containerized ML systems.
• Master’s or Doctoral Degree in Computer Science, Electrical Engineering, Mathematics, or a related field.
• 5+ years optimizing ML algorithms, configurations, and infrastructure.
• 5+ years following software development best practices including source control, testing, code reviews, and CI/CD.
• 5+ years building resilient software with pre-production testing, advanced deployment techniques (one-box, blue/green, gradual dial-up), monitoring, alarms, and incident response planning.
• 5+ years working with ML techniques (Supervised, semi-supervised, and unsupervised, reinforcement learning, etc.) across model types (Regression, Classification, Clustering, etc.) and architectures (RNNs, CNNs, LSTMs, Transformers), including training concepts and diagnosing underfitting/overfitting.
• 5+ years designing, implementing, and scaling production-ready data pipelines for training and evaluating ML models.
• ML industry impact through conference presentations, papers, blog posts, open source contributions, or patents.
• Ability to communicate complex technical and machine learning concepts clearly to a variety of audiences.

Technologies

• Python, Scala, Java, Golang, C++, PyTorch, Tensorflow
• Pandas, NumPy, Scikit-learn
• Spark, Ray, AWS, GCP, Azure, Kubernetes
• CI/CD, RNNs, CNNs, LSTMs, Transformers

Accommodations and recruiting contact

If you visited our website to search for information on employment opportunities or to apply for a position and require accommodations, contact 1-800-304-9102 or [email protected].

For technical support or questions about Capital One’s recruiting process, email [email protected].