Machine Learning Engineer 5 (Senior Manager, IC)

Capital One is seeking a Machine Learning Engineer to design, build, and scale machine learning models and platforms that move from development into production. In this role, you will help deliver ML solutions across modeling, data engineering, and operations, including deployment, monitoring, and retraining at scale.

This position is based in New York, NY (onsite) and targets an experienced engineer with a strong background in ML engineering, distributed systems, and production software practices. The salary range for this role is USD 250,800 - 286,200 per year.

What you’ll do

• Design, build, and/or deliver ML models and components that address real-world business problems in collaboration with Product and Data Science.
• Build and scale massive multi-tenant platforms for large footprint ML model training and/or serving.
• Apply ML modeling knowledge to influence infrastructure decisions, including model and data/feature selection, training, hyperparameter tuning, dimensionality, and validation, with attention to bias/variance.
• Solve complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment.
• Work within a cross-functional Agile team to create and improve software powering state-of-the-art big data and ML applications.
• Retrain, maintain, and monitor models in production.
• Use or build cloud-based architectures and platforms to deliver optimized ML models at scale.
• Construct optimized data pipelines that feed ML models.
• Use CI/CD best practices, including test automation and monitoring, to support reliable deployment of ML models and application code.
• Help ensure code is well-managed to reduce vulnerabilities, models are well-governed from a risk perspective, and ML systems follow Responsible and Explainable AI best practices.
• Use programming languages such as Python, Scala, or Java.

Required qualifications

• Bachelor’s Degree or higher in Computer Science, Machine Learning, or a related quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Engineering).
• 6+ years programming with Python, Java, Golang, or C++.
• 6+ years Machine Learning experience using PyTorch or TensorFlow and libraries such as Pandas, NumPy, Scikit-learn.
• 6+ years experience using and operating large scale distributed systems (including Spark and Ray) to prepare AI/ML data.
• 4+ years deploying and operating ML solutions in production and operating production services in the cloud (AWS, GCP, Azure), including using Kubernetes to manage containerized ML systems at scale.
• Master’s or Doctoral Degree in Computer Science, Electrical Engineering, Mathematics, or 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 and alarms, and incident response plan preparation.
• 5+ years applying ML techniques (Supervised, semi-supervised, and unsupervised learning, reinforcement learning, etc.) across model types and architectures including Regression, Classification, Clustering, and RNNs, CNNs, LSTMs, Transformers, along with concepts for training (loss function, hyperparameters, regularization) and model evaluation to diagnose issues such as underfitting and overfitting.
• 5+ years designing, implementing, and scaling production-ready data pipelines for training and evaluating ML models.
• Demonstrated 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

Compensation and benefits

• Eligible for performance-based incentive compensation, which may include cash bonus(es) and/or long-term incentives (LTI).
• Comprehensive, competitive, and inclusive health, financial, and other benefits supporting total well-being.

Salary information by location

• Cambridge, MA: $229,900 - $262,400
• McLean, VA: $229,900 - $262,400
• New York, NY: $250,800 - $286,200
• San Francisco, CA: $250,800 - $286,200
• San Jose, CA: $250,800 - $286,200

Recruiting support

• If you visited the website seeking information on employment opportunities or to apply and require accommodation: 1-800-304-9102 or [email protected].
• For technical support or questions about Capital One’s recruiting process: [email protected].