Machine Learning Engineer 5

Capital One is hiring a Machine Learning Engineer 5 (Senior Manager, IC) to support Risk Tech, where the team builds and deploys proprietary, AI-powered risk management solutions. Working with the GRC team and partners, you will help advance machine learning model development and production operations, with an emphasis on responsible and explainable AI.

This role is based in McLean, VA (onsite) and includes a salary range of USD 229,900 - 262,400 per year. Capital One requires a strong foundation in machine learning, scalable platforms, and cloud production practices, along with demonstrated experience delivering and operating ML systems.

Responsibilities

• Design, build, and/or deliver ML models and components to address real business needs in partnership with Product and Data Science teams
• Build and scale large multi-tenant platforms to support ML model training and serving at scale
• Guide ML infrastructure choices using expertise across modeling and experimentation, including model selection, data and feature selection, training, hyperparameter tuning, dimensionality, bias/variance, and validation
• Solve complex problems through application code development, model development and validation, and automation of tests and deployment
• Collaborate in a cross-functional Agile environment to create and improve big data and ML software capabilities
• 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
• Apply CI/CD best practices, including test automation and monitoring, to support successful ML model and application deployments
• Manage code to reduce vulnerabilities, ensure risk-governed models, and follow Responsible and Explainable AI best practices
• Use programming languages such as Python, Scala, or Java

Requirements

• 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 programming with Python, Java, Golang, or C++
• At least 6 years Machine Learning experience using PyTorch or Tensorflow and libraries including Pandas, NumPy, Scikit-learn
• At least 6 years experience using and operating large-scale distributed systems such as Spark and Ray to prepare AI/ML data
• At least 4 years deploying and operating Machine Learning solutions in production, including cloud operations on AWS, GCP, or Azure and using Kubernetes for large-scale containerized ML systems

Preferred Qualifications

• 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 such as 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 preparation
• 5+ years hands-on experience with ML techniques (supervised, semi-supervised, unsupervised, reinforcement learning) and model types (regression, classification, clustering), model architectures (RNNs, CNNs, LSTMs, Transformers), and training concepts (loss function, hyperparameters, regularization), including evaluating accuracy and diagnosing common issues (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 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, Agile

Benefits

• Performance-based incentive compensation, which may include cash bonus(es) and/or long-term incentives (LTI)
• A comprehensive, competitive, and inclusive set of health, financial, and other benefits supporting total well-being

Additional information: Capital One may sponsor a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries vary by location, including McLean, VA: $229,900 - $262,400 (and Richmond, VA: $209,000 - $238,500). Capital One expects to accept applications for at least 5 business days. No agencies please. Capital One is an equal opportunity employer committed to non-discrimination in compliance with applicable federal, state, and local laws and promotes a drug-free workplace. Capital One will consider qualified applicants with criminal history consistent with applicable laws. If you need accommodation, contact Capital One Recruiting at 1-800-304-9102 or [email protected]. For technical support or questions about recruiting, email [email protected].