Senior ML Platform Engineer — IC Lead

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

Job summary

Capital One is seeking a Machine Learning Engineer 4 to join the Enterprise ML Platform. You will build and scale high-throughput, multi-tenant training platforms powering model workflows, from classical ML to GenAI fine-tuning, using Ray, Spark, and Dask on Amazon EKS.

You will integrate agentic AI into modern engineering lifecycles and contribute to Kubeflow upstreams while maintaining security and governance.

Qualifications

• Bachelor's degree or higher in CS, ML or related quantitative field.
• 4+ years coding in Python, Java, Golang or C++.
• 4+ years ML experience with PyTorch or TensorFlow.
• 4+ years operating large-scale distributed systems (Spark, Ray).
• 2+ years deploying ML solutions in production and cloud (AWS, GCP, Azure) with Kubernetes.

Responsibilities

• Design, build, and deliver ML models and components with product and data science teams.
• Inform infrastructure decisions using ML modeling techniques and data choices.
• Write, test, and deploy application code for ML solutions.
• Collaborate in an Agile team to create software for big data and ML apps.
• Retrain, maintain, and monitor models in production.
• Leverage cloud architectures to deliver ML models at scale.
• Construct data pipelines feeding ML models.
• Apply CI/CD, test automation, monitoring for reliable deployments.
• Ensure governance and responsible AI practices in models and code.
• Use Python, Scala, or Java for development.

Skills

Python

Java

Golang

C++

PyTorch

TensorFlow

Education

Bachelor's degree in CS or related field

Master's degree preferred

Tools

Spark

Ray

Kubernetes

Kubeflow

Kubeflow Pipelines

Job description

Capital One is seeking a Machine Learning Engineer 4 to join the Enterprise ML Platform. You will build and scale high-throughput, multi-tenant training platforms powering model workflows, from classical ML to GenAI fine-tuning, using Ray, Spark, and Dask on Amazon EKS.

You will integrate agentic AI into modern engineering lifecycles and contribute to Kubeflow upstreams while maintaining security and governance.