Lead Machine Learning Engineer

Capital One Financial

Confirmed live yesterday Low trust

Quick summary

Work type: On-site
Location: McLean, VASan Francisco, CACambridge, MASan Jose, CANew York, NY
Employment: Full-time
Posted: 49 days ago
Freshness: Confirmed live yesterday
Nearby: 99+ roles within 25 mi

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Salary context

How this pay compares to similar roles

Similar $225k

$174k $274k

below market most similar roles pay here above market

This listing doesn't post a salary. Most similar roles pay $200,437–$249,000.

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 2107 open roles on FindRole.

Listed pay typically runs $197,300–$225,100 across 1107 roles with salary data.

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At a glance

TL;DR · Lead Machine Learning Engineer

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The Lead Machine Learning Engineer (Python, GoLang, AWS) joins an Agile team focused on productionizing machine learning applications and systems at scale. This role involves participating in technical designs, developing model and application code, and ensuring high availability and performance. Key responsibilities include building ML models to solve business problems, constructing optimized data pipelines, and managing cloud-based architectures. The engineer will retrain, maintain, and monitor models while automating tests and deployments using continuous integration and continuous deployment best practices. The position requires proficiency in Python, Scala, or Java, along with experience in distributed computing and ML systems. The work centers on solving complex problems through model training, hyperparameter tuning, and ensuring Responsible and Explainable AI within a production environment.

Skills

Python GoLang AWS Scala Java Machine Learning Distributed Computing Data Pipelines Agile Test Automation Explainable AI

What you'll do

Design, build, and deliver machine learning models and components to solve real-world business problems.
Write and test application code to develop, validate, and automate the deployment of ML models.
Retrain, maintain, and monitor machine learning models in production environments.
Construct optimized data pipelines to feed machine learning models.
Build and leverage cloud-based architectures and technologies to deliver optimized models at scale.
Implement continuous integration and continuous deployment best practices, including test automation and monitoring.
Ensure all code and models follow best practices for Responsible and Explainable AI.

What we're looking for

At least 6 years of experience designing and building data-intensive solutions using distributed computing.
At least 4 years of experience programming with Python, Scala, or Java.
At least 2 years of experience building, scaling, and optimizing ML systems.
Master's or Doctoral Degree in computer science, electrical engineering, mathematics, or a similar field (preferred).
3+ years of experience building production-ready data pipelines that feed ML models (preferred).

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