Capital One is hiring a senior-level Machine Learning Engineer to build and deploy proprietary, AI-powered risk management solutions.

Design, build, and/or deliver ML models and components to solve real business problems in collaboration with Product and Data Science teams
Build and scale large multi-tenant platforms for large-footprint ML training and/or serving
Guide ML infrastructure decisions using knowledge of ML modeling topics such as model choice, data and feature selection, 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
Work in a cross-functional Agile team to create and improve software enabling big data and ML applications
Retrain, maintain, and monitor ML models in production
Leverage and/or build cloud-based architectures, technologies, and platforms to deliver optimized ML models at scale
Construct optimized data pipelines to feed ML models
Apply 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, govern ML from a risk perspective, and apply Responsible and Explainable AI best practices
Use programming languages including Python, Scala, or Java

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 Machine Learning experience using industry-standard frameworks PyTorch or Tensorflow and libraries Pandas, NumPy, Scikit-learn
At least 6 years of experience using and operating large-scale distributed systems (e.g., Spark, Ray) to prepare AI/ML data
At least 4 years of experience deploying and operating ML solutions in production, including operating production services in the cloud (AWS, GCP, Azure) and using Kubernetes to manage large-scale containerized ML systems

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 supporting total well-being

Master's or doctoral degree in computer science, electrical engineering, mathematics, or related field
5+ years of experience optimizing ML algorithms, configurations, and infrastructure
5+ years of experience following software development best practices including source control, testing, code reviews, and CI/CD
5+ years of experience building resilient software solutions with pre-production testing, advanced deployment techniques (one-box, blue/green, gradual dial-up), monitoring, alarms, and incident response plan preparation
5+ years of experience with ML techniques (supervised, semi-supervised, unsupervised, reinforcement learning, etc.), model types (regression, classification, clustering, etc.), model architectures (RNNs, CNNs, LSTMs, Transformers), and training/evaluation concepts (loss function, hyperparameters, regularization, diagnosing underfitting and overfitting)
5+ years of experience 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 ML concepts clearly to a variety of audiences

Location: McLean, VA (onsite)
Salary (USD): $229,900 - $262,400 per year
Capital One will consider sponsoring a new qualified applicant for employment authorization for this position
Expected application review window: minimum of 5 business days
No agencies please
Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination
Capital One promotes a drug-free workplace
Capital One will consider qualified applicants with a criminal history consistent with applicable law
Accommodation request: 1-800-304-9102 or [email protected]
Recruiting process technical questions: [email protected]

Machine Learning Engineer 5

Job Description