Machine Learning Engineer 4

Capital One’s Enterprise Platforms Technology team builds important enterprise capabilities and establishes practices for delivering technology solutions across the company. In this onsite role in Plano, TX, you will help design, build, and scale production AI and machine learning models and the platforms that run them.

This position spans the full ML engineering lifecycle, including model development, data pipelines, deployment, monitoring, and Responsible and Explainable AI governance. You will also work closely with Product and Data Science partners within an Agile delivery environment.

What you’ll do

• Design, build, and/or deliver ML models and components to address real business problems with collaboration across Product and Data Science teams
• Apply ML modeling knowledge to guide infrastructure decisions, including model and data selection, feature selection, training, hyperparameter tuning, dimensionality considerations, bias/variance tradeoffs, and validation strategy
• Address complex challenges through application development, ML model development and validation, and automation of tests and deployment workflows
• Contribute within a cross-functional Agile team to create and improve software supporting big data and ML application development
• Retrain, maintain, and monitor models in production
• Leverage and/or build cloud-based architectures, technologies, and platforms to deliver optimized ML models at scale
• Create optimized data pipelines that feed ML models
• Use continuous integration and continuous deployment best practices, including test automation and monitoring, to support successful releases of ML models and application code
• Manage code to reduce vulnerabilities, support risk-governed model practices, and ensure ML follows best practices in Responsible and Explainable AI
• Use programming languages including Python, Scala, or Java

What you bring

• 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 of experience working with and operating large-scale distributed systems (including Spark and Ray) to prepare AI/ML data
• At least 2 years 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 software systems

Tools and technologies

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

Team context

• The Enterprise Platforms Technology (EPTech) team comprises many of Capital One’s most important enterprise platforms
• EPTech plays an essential role in establishing practices for building technology solutions across the company, while delivering capabilities that exemplify those practices
• The Marketing and Messaging team delivers hyper-personalized messages and experiences, builds scalable omnichannel platforms, and supports owned and paid Adtech channels

Compensation

Estimated salary range for Plano, TX: USD 179,400 - 204,700 per year.

Benefits

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

Additional information

• Preferred qualifications include a Master’s or Doctoral Degree in Computer Science, Electrical Engineering, Mathematics, or a related field, along with multiple years of experience optimizing ML algorithms and configurations, following software development best practices, and building production-ready data pipelines, among other criteria
• Immigration / work authorization statement: Capital One will not sponsor a new applicant for employment authorization and will not offer immigration-related support for this position
• Accommodation and contact information: If you require an accommodation, contact Capital One Recruiting at 1-800-304-9102 or via email at [email protected]. For technical support or questions about Capital One’s recruiting process, email [email protected]