Senior ML Engineer, Real-Time Personalization Platform

Capital One; Honolulu (HI); Remote; USD 286,000 - 359,000; Full time

Job summary

Capital One is seeking a Sr. Staff Machine Learning Engineer (Remote-Eligible) to lead the personalization platform, shaping real-time, cohort-of-one experiences across Capital One products.

You will build scalable ML infrastructure, develop a flexible rules engine, and drive advanced ML optimization techniques with a broad open-source stack. You will mentor engineers, influence architecture, and partner across product, data science, and cloud infrastructure teams to deliver high-performance,

Qualifications

• Bachelor’s degree in a technical field.
• 10+ years of experience designing data-intensive solutions using distributed computing.
• 5+ years of experience with ML architectures and production deployment.

Responsibilities

• Define and drive technical strategy and roadmap for a personalization platform.
• Collaborate with product, data science, cloud infra, and ML platform teams.
• Develop scalable ML infrastructure and end-to-end pipelines for feature extraction, training, testing, and deployment.
• Architect low-latency event-driven systems for real-time personalization and decisioning.
• Advance MLOps practices with automated deployment, testing, and monitoring workflows.
• Investigate and apply state-of-the-art optimization techniques for large-scale AI systems.

Skills

Distributed computing

Python

C++

Java

Golang

PyTorch

TensorFlow

Databricks

Airflow

Kubeflow

Docker

Kubernetes

Education

Bachelor’s degree

Master’s or PhD in Computer Science or relevant field

Tools

AWS

GCP

Azure

Huggingface

VectorDBs

Nemo Guardrails

Job description

Capital One is seeking a Sr. Staff Machine Learning Engineer (Remote-Eligible) to lead the personalization platform, shaping real-time, cohort-of-one experiences across Capital One products.

You will build scalable ML infrastructure, develop a flexible rules engine, and drive advanced ML optimization techniques with a broad open-source stack. You will mentor engineers, influence architecture, and partner across product, data science, and cloud infrastructure teams to deliver high-performance,