Machine Learning Engineer 5

Capital One is seeking a Machine Learning Engineer 5 to design, build, scale, deploy, and monitor machine learning models and platforms that address real business needs. In this onsite role in Richmond, VA, you will help shape ML infrastructure and delivery practices across model lifecycle activities, from data pipelines to production operations, with a focus on Responsible and Explainable AI.

What you’ll do

• Design, build, and deliver machine learning models and components in collaboration with Product and Data Science teams
• Build and scale massive multi-tenant platforms for large-footprint ML training and/or serving at scale
• Guide ML infrastructure decisions using expertise in modeling topics such as model and data selection, 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 within a cross-functional Agile team 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 platforms to deliver optimized ML models at scale
• Create optimized data pipelines to feed ML models
• Apply CI/CD best practices, including test automation and monitoring, to support successful deployments
• Manage code to reduce vulnerabilities, support risk-governed model practices, 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 of experience programming with Python, Java, Golang, or C++
• At least 6 years of machine learning experience using PyTorch or TensorFlow and libraries including Pandas, NumPy, and Scikit-learn
• At least 6 years of experience using and operating large-scale distributed systems (Spark, Ray) to prepare AI/ML data
• At least 4 years of experience deploying and operating machine learning solutions in production and operating production services in the cloud (AWS, GCP, Azure), using Kubernetes for large-scale containerized ML systems

Technology stack

• Python, Scala, Java, Golang, C++
• PyTorch, TensorFlow, Pandas, NumPy, Scikit-learn
• Spark, Ray, AWS, GCP, Azure, Kubernetes
• CI/CD, continuous integration, continuous deployment

Compensation & benefits

Salary: USD 209,000 - 238,500 per year for Richmond, VA.

• Eligible for 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

Preferred qualifications

• 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 and model types, including supervised, semi-supervised, and unsupervised learning, reinforcement learning, regression, classification, and clustering, as well as architectures such as RNNs, CNNs, LSTMs, and Transformers
• 5+ years of experience with training concepts such as loss function, hyperparameters, regularization, plus evaluating model accuracy and diagnosing issues like 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 machine learning concepts clearly to a variety of audiences

Additional information

• Capital One will consider sponsoring a new qualified applicant for employment authorization for this position
• Expected to accept applications for a minimum of 5 business days
• No agencies please; Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws
• Capital One promotes a drug-free workplace
• Capital One will consider for employment qualified applicants with a criminal history consistent with applicable laws regarding criminal background inquiries
• Accommodation contact: Capital One Recruiting at 1-800-304-9102 or [email protected]
• Technical support/questions: [email protected]
• Capital One does not provide, endorse, or guarantee third-party products, services, educational tools, or other information available through this site

Salary range note: Machine Learning Engineer 5 salary ranges are also listed for other locations (McLean, VA; New York, NY; Plano, TX), and Richmond, VA is USD 209,000 - 238,500 per year.