Senior Lead Machine Learning Engineer

Capital One Financial

Confirmed live 2 days ago Low trust

Quick summary

Work type: On-site
Location: McLean, VASan Francisco, CARichmond, VANew York, NY
Salary: $229,900–$262,400 / yr
Posted: 72 days ago
Freshness: Confirmed live 2 days ago
Nearby: 99+ roles within 25 mi

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $225k

This role $246k

$175k most similar roles pay here $275k

This role pays more than 68% of similar roles. Most pay $195,112–$254,750 — the shaded band above. At the midpoint, this role pays about $246k versus about $225k 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 998 open roles on FindRole.

Listed pay typically runs $197,300–$225,100 across 992 roles with salary data.

Most-posted roles

View all roles at Capital One Financial

At a glance

TL;DR · Senior Lead Machine Learning Engineer

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As a Sr. Lead Machine Learning Engineer, you will join an Agile team dedicated to productionizing machine learning applications and systems at scale. You will be responsible for the technical design, development, and implementation of ML models and components that solve real-world business problems. Your daily work involves building and maintaining optimized data pipelines, managing model retraining, and ensuring high availability through automated testing and CI/CD practices. You will focus on architectural design while ensuring models follow best practices in Responsible and Explainable AI. The role requires proficiency in Python, Scala, or Java, along with experience in frameworks like scikit-learn, PyTorch, Dask, Spark, or TensorFlow. You will also leverage cloud-based architectures to deliver high-performance solutions within a complex technical environment involving big data and advanced machine learning engineering.

Skills

Machine Learning Python Scala Java Spark PyTorch TensorFlow scikit-learn Dask AWS Azure Google Cloud Platform Data Pipelines Distributed Computing Agile Explainable AI

What you'll do

Design, build, and deliver machine learning models and components that solve real-world business problems.
Develop and review model and application code while ensuring high availability and performance of ML systems.
Construct optimized data pipelines to feed machine learning models.
Retrain, maintain, and monitor machine learning models in production environments.
Build or leverage cloud-based architectures and technologies to deliver optimized models at scale.
Implement CI/CD best practices, including test automation and monitoring, for model and code deployment.
Ensure all code is managed to reduce vulnerabilities and follows Responsible and Explainable AI principles.

What we're looking for

Bachelor's degree required; Master's or Doctoral degree in a related field preferred.
At least 8 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 3 years of experience building, scaling, and optimizing ML systems.
At least 2 years of experience leading teams developing ML solutions.
At least 4 years of experience with industry-recognized ML frameworks like scikit-learn, PyTorch, Dask, Spark, or TensorFlow.
At least 3 years of experience building production-ready data pipelines and gathering/preparing data for ML models.
Experience deploying ML solutions in public clouds such as AWS, Azure, or Google Cloud Platform.

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