Sr Lead Machine Learning Engineer

Capital One Financial

Quick summary

Work type: On-site
Location: McLean, VA
Salary: $229,900–$262,400 / yr
Posted: 5 days ago
Nearby: 99+ roles within 25 mi

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $222k

This role $246k

$162k most similar roles pay here $275k

This role pays more than 69% of similar roles. Most pay $194,500–$249,750 — the shaded band above. At the midpoint, this role pays about $246k versus about $222k for comparable roles.

Based on 240 similar postings.

Employer

About Capital One Financial

Capital One Financial is a bank holding company specializing in credit cards, auto loans, banking, and savings products, known for its data-driven approach to consumer and commercial finance. Industry: Financial Services & Banking

Capital One Financial currently has 814 open roles on FindRole.

Listed pay typically runs $197,300–$225,100 across 809 roles with salary data.

Most-posted roles

View all roles at Capital One Financial

At a glance

TL;DR · Sr Lead Machine Learning Engineer

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As a Senior Lead Machine Learning Engineer in this specialized group, you will play a pivotal role in developing and maintaining the decisioning technology that guides customers through their credit journey. Your responsibilities include building, deploying, and monitoring complex machine learning models at scale to reduce friction for data science teams. Utilizing Python and Kubernetes, your day-to-day work involves creating robust infrastructure that supports real-time interactions with millions of users from application submission to account closure. This role requires expertise in modern cloud technologies, proficiency in Python, and a strong understanding of machine learning model deployment and monitoring practices.

Skills

Python Kubernetes AWS CI/CD Docker Prometheus Grafana PostgreSQL Git Scikit-learn TensorFlow PyTorch

What you'll do

Develop and maintain machine learning models for customer decisioning processes.
Standardize and streamline the deployment of complex ML models at scale.
Monitor and optimize ML infrastructure to support millions of customers in real time.
Utilize Python and Kubernetes to build high-impact, scalable technology solutions.
Collaborate with data science teams to reduce friction in model development.

What we're looking for

Minimum 7 years of experience in machine learning engineering or related field.
Proficient in Python and Kubernetes for building scalable ML infrastructure.
Experience with deploying and monitoring complex models at scale required.
Strong background in data science and decision-making technology systems.
Bachelor’s Degree in Computer Science, Engineering, Mathematics, or Statistics.
Ability to support millions of customers in real-time throughout their lifecycle.

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