Machine Learning Engineer 4

Capital One is seeking a Machine Learning Engineer 4 to support Enterprise Platforms Technology (EPTech) and the Marketing and Messaging team. The role focuses on designing, building, deploying, and monitoring machine learning models and pipelines at scale using cloud architectures and responsible AI practices.

Role Summary

This position supports ML initiatives across EPTech and the Marketing and Messaging organization. Responsibilities include developing model and pipeline solutions, operating production ML services, and ensuring deployment quality through CI/CD and monitoring practices.

Responsibilities

• Design, build, and deliver machine learning models and components that address real-world business needs in collaboration with Product and Data Science teams.
• Guide ML infrastructure decisions using expertise in modeling and evaluation 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 that supports state-of-the-art big data and ML applications.
• Retrain, maintain, and monitor models after deployment in production environments.
• Leverage or build cloud-based architectures, technologies, and platforms to deliver optimized ML models at scale.
• Construct optimized data pipelines to supply ML models.
• Apply continuous integration and continuous deployment best practices, including test automation and monitoring, to support reliable deployment of ML models and application code.
• Manage code to reduce vulnerabilities, support risk-governed model practices, and follow best practices for Responsible and Explainable AI.
• Use programming languages such as Python, Scala, or Java in daily engineering work.

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 4 years of experience programming with Python, Java, Golang, or C++.
• At least 4 years of machine learning experience using industry-standard frameworks PyTorch or Tensorflow and libraries such as Pandas, NumPy, Scikit-learn.
• At least 4 years using and operating large-scale distributed systems (such as Spark, Ray) to prepare AI/ML data.
• At least 2 years deploying and operating ML solutions in production and operating production services in the cloud (AWS, GCP, Azure), including Kubernetes for large-scale containerized ML systems.
• Master’s or Doctoral Degree in Computer Science, Electrical Engineering, Mathematics, or a related field.
• 3+ years optimizing ML algorithms, configurations, and infrastructure.
• 3+ years following software development best practices including source control, testing, code reviews, and CI/CD.
• 3+ 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.
• 3+ years working with ML techniques (Supervised, semi-supervised, and unsupervised, reinforcement learning) and model types (Regression, Classification, Clustering), including architectures (RNNs, CNNs, LSTMs, Transformers), training concepts (loss function, hyperparameters, regularization), and evaluating model accuracy while diagnosing underfitting and overfitting.
• 3+ years designing, implementing, and scaling production-ready data pipelines for training and evaluating ML models.
• 1+ year experience as a technical lead developing ML solutions using industry best practices, patterns, and automation.
• Authored or co-authored a paper on a machine learning technique, model, or proof of concept.

Technologies

• Python, Scala, Java, Golang, C++
• AWS, GCP, Azure, Kubernetes
• PyTorch, Tensorflow, Pandas, NumPy, Scikit-learn
• Spark, Ray
• CI/CD
• RNNs, CNNs, LSTMs, Transformers

Team

The Marketing and Messaging team delivers hyper-personalized messages and experiences designed to delight the customer, attract prospects, and drive increasing business value. The team builds scalable platforms that deliver omnichannel messages across owned and paid Adtech channels.

Location and Salary

Location: New York, NY (onsite). The yearly salary range for this role in New York, NY is USD 215,200 - 245,600.

Benefits

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

Additional Compensation Notes by Location

• McLean, VA: $197,300 - $225,100
• New York, NY: $215,200 - $245,600
• Plano, TX: $179,400 - $204,700
• Richmond, VA: $179,400 - $204,700
• San Francisco, CA: $215,200 - $245,600
• Candidates hired in other locations will receive the pay range associated with that location.

Entity Information

• Positions posted in Canada are for Capital One Canada.
• Positions posted in the United Kingdom are for Capital One Europe.
• Positions posted in the Philippines are for Capital One Philippines Service Corp. (COPSSC).