Build and deploy AI-powered risk management solutions by designing ML models, scalable platforms, and production-ready pipelines.

Design, build, and/or deliver machine learning models and components to address real-world business problems with Product and Data Science
Build and scale massive multi-tenant platforms for large-footprint ML model training and/or serving
Drive ML infrastructure decisions using knowledge of modeling techniques and considerations, including 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
Collaborate in cross-functional Agile teams to create and enhance software for 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
Apply continuous integration and continuous deployment best practices, including test automation and monitoring, for successful deployment of ML models and application code
Manage code to reduce vulnerabilities; ensure risk-governed models and adherence to 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 operating and using large scale distributed systems (Spark, Ray) to prepare AI/ML data
At least 4 years deploying and operating machine learning solutions in production, including cloud production services (AWS, GCP, Azure) and using Kubernetes to manage 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 plan preparation
5+ years working with machine learning techniques (Supervised, semi-supervised, unsupervised, reinforcement learning) and model types (Regression, Classification, Clustering)
5+ years working with model architectures (RNNs, CNNs, LSTMs, Transformers) and training concepts (loss function, hyperparameters, regularization), including evaluating accuracy and diagnosing underfitting and 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

Eligible to earn performance-based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI)
Incentives may be discretionary or non-discretionary depending on the plan

Applications expected to accept for a minimum of 5 business days
No agencies please
Equal opportunity employer (EOE, including disability/vet) committed to non-discrimination under applicable laws
Drug-free workplace
Considering qualified applicants with criminal history consistent with applicable laws

Capital One will consider sponsoring a new qualified applicant for employment authorization for this position

Accommodation request contact: Capital One Recruiting at 1-800-304-9102 or [email protected]
Technical support/questions: [email protected]

Machine Learning Engineer 5 (Senior Manager, IC)

Job Description