Senior ML Engineer & Tech Lead – Production AI

Capital One National Association; New York (NY); On-site; USD 215,000 - 246,000; Full time

Job summary

Capital One National Association is seeking a Machine Learning Engineer to design, build, and deploy ML models and supporting infrastructure. Collaborate with a cross-functional team across product and data science, and responsibly deploy models in production using cloud platforms and container orchestration.

The role emphasizes model governance, monitoring, and scalable data pipelines, with production-grade code and CI/CD practices across Python, Scala, or Java.

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 standard frameworks PyTorch or Tensorflow and libraries (Pandas, NumPy, Scikit-learn)
• At least 4 years of experience using and operating large scale distributed systems (Spark, Ray) to prepare AI or Machine Learning data
• At least 2 years of experience deploying and operating Machine Learning solutions in production and operating production services in the cloud (AWS, GCP, Azure) and using Kubernetes to manage large scale containerized Machine Learning software systems

Responsibilities

• Design, build, and/or deliver ML models and components that solve real-world business problems, collaborating with Product and Data Science teams
• Inform ML infrastructure decisions with understanding of modeling techniques, data, feature selection, training, tuning, and validation
• Solve complex problems by writing and testing code, developing ML models, and automating tests and deployment
• Collaborate in an Agile cross-functional 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 to deliver optimized ML models at scale
• Construct optimized data pipelines to feed ML models
• Use CI/CD, test automation, and monitoring for successful deployment
• Ensure code quality, governance, and responsible/Explainable AI practices
• Use Python, Scala, or Java for development

Skills

Python

Java

Golang

C++

ML engineering

Education

Bachelor’s degree in CS/ML or related field

Master’s/Doctoral degree preferred

Tools

PyTorch

TensorFlow

Spark

Ray

Kubernetes

Job description

Capital One National Association is seeking a Machine Learning Engineer to design, build, and deploy ML models and supporting infrastructure. Collaborate with a cross-functional team across product and data science, and responsibly deploy models in production using cloud platforms and container orchestration.

The role emphasizes model governance, monitoring, and scalable data pipelines, with production-grade code and CI/CD practices across Python, Scala, or Java.