Machine Learning Engineer 4

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

Role Summary

As part of the EPTech and Marketing and Messaging organizations, you will contribute to real-world machine learning solutions by developing model and pipeline components, optimizing infrastructure decisions, and ensuring models are maintained and monitored in production environments.

Responsibilities

• Design, build, and/or deliver machine learning models and components that address business needs in collaboration with Product and Data Science teams
• Drive ML infrastructure decisions using knowledge of modeling considerations such as model choice, data and feature selection, model training, hyperparameter tuning, dimensionality, bias/variance, and validation
• Solve complex problems through application development, model development and validation, and automation of tests and deployments
• Collaborate within a cross-functional Agile team to create and improve software enabling state-of-the-art 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 that supply ML models
• Apply continuous integration and continuous deployment practices, including test automation and monitoring, to support successful deployment of ML models and application code
• Manage code to reduce vulnerabilities, ensure models are governed from a risk perspective, and follow Responsible and Explainable AI best practices
• Use programming languages including Python, Scala, or Java

Required Qualifications

• 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 frameworks PyTorch or Tensorflow and libraries including Pandas, NumPy, and Scikit-learn
• At least 4 years using and operating large scale distributed systems (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 using Kubernetes to manage large scale containerized ML software 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 solutions with pre-production testing, advanced deployment approaches (one-box, blue/green, gradual dial-up), monitoring, alarms, and incident response planning
• 3+ years applying machine learning techniques including supervised, semi-supervised, and unsupervised learning, and reinforcement learning, including model types (Regression, Classification, Clustering) and architectures (RNNs, CNNs, LSTMs, Transformers), plus training and evaluation concepts such as loss function, hyperparameters, regularization, and diagnosing underfitting and overfitting
• 3+ years designing, implementing, and scaling production-ready data pipelines for training and evaluating ML models
• 1+ years experience as a technical lead developing ML solutions using industry best practices, patterns, and automation
• Authored or co-authored a paper on an ML 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 Information

The Marketing and Messaging team delivers hyper-personalized messages and experiences that support customer attraction and increasing business value. The team also builds scalable platforms that deliver omnichannel messages in owned and paid Adtech channels.

Location and Compensation

Location: New York, NY (onsite)

Base salary range: USD 215,200 - 245,600 per year

• 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 to work in other locations will be subject to the pay range associated with that location.

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 Entity Information

• Any position posted in Canada is for Capital One Canada
• Any position posted in the United Kingdom is for Capital One Europe
• Any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC)