Senior Machine Learning Engineer, Foundations & Production

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

Job summary

Capital One is seeking a Machine Learning Engineer 4 – MLX in New York, NY to design, build, and productionize ML models and data pipelines. You will collaborate with Product and Data Science teams to solve real business problems using PyTorch, TensorFlow, and distributed systems like Spark/Ray, deploying on AWS/GCP/Azure with Kubernetes support.

The role emphasizes building scalable ML solutions, training and validating models, monitoring production systems, and adhering to responsible AI

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 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, Google Cloud Platform, 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, while collaborating with Product and Data Science teams
• Inform ML infrastructure decisions with understanding of modeling techniques, data, feature selection, training, tuning, validation
• Write and test application code, develop and validate ML models, and automate tests and deployment
• Collaborate in a cross-functional Agile team to create and enhance software for state-of-the-art big data and ML applications
• Retrain, maintain, and monitor models in production
• Leverage cloud-based architectures to deliver optimized ML models at scale
• Construct optimized data pipelines to feed ML models
• Use CI/CD and monitoring to ensure successful deployment of ML models and code
• Ensure code is well-governed from a risk perspective and follows Responsible AI practices
• Use programming languages like Python, Scala, or Java

Skills

Python

Java

Golang

C++

PyTorch

TensorFlow

Pandas

NumPy

Scikit-learn

Spark

Ray

AWS

GCP

Azure

Kubernetes

Education

Bachelor's degree or higher

Tools

Kubernetes

Job description

Capital One is seeking a Machine Learning Engineer 4 – MLX in New York, NY to design, build, and productionize ML models and data pipelines. You will collaborate with Product and Data Science teams to solve real business problems using PyTorch, TensorFlow, and distributed systems like Spark/Ray, deploying on AWS/GCP/Azure with Kubernetes support.

The role emphasizes building scalable ML solutions, training and validating models, monitoring production systems, and adhering to responsible AI