Senior Lead Machine Learning Engineer

Capital One Financial

Confirmed live yesterday Low trust

Quick summary

Work type: On-site
Location: McLean, VARichmond, VANew York, NYPlano, TX
Salary: $229,900–$262,400 / yr
Posted: 50 days ago
Freshness: Confirmed live yesterday
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 $272k

This role pays more than 71% of similar roles. Most pay $195,150–$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

Role Posting Log in to save

As a Senior 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 machine learning architectures while ensuring high availability and performance. Your daily work involves building and delivering models that solve real-world business problems, constructing optimized data pipelines, and managing model retraining and monitoring in production environments. You will collaborate with cross-functional teams to develop software for big data applications while adhering to principles of Responsible and Explainable AI. The role requires proficiency in Python, Scala, or Java, along with experience using frameworks such as scikit-learn, PyTorch, Dask, Spark, or TensorFlow. You will also leverage cloud-based architectures to deliver optimized models and manage the full lifecycle of model deployment and automated testing.

Skills

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

What you'll do

Design and implement machine learning architectures and applications using emerging technology platforms.
Develop, test, and validate model code while automating testing and deployment processes.
Construct optimized data pipelines to feed machine learning models.
Retrain, maintain, and monitor machine learning models in production environments.
Build and manage cloud-based infrastructures to deliver optimized models at scale.
Implement CI/CD best practices, including test automation and monitoring for all application code.
Ensure model governance by following best practices in Responsible and Explainable AI.

What we're looking for

Bachelor's degree required; Master's or doctoral degree in a relevant 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 an industry recognized ML framework 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 a public cloud such as AWS, Azure, or Google Cloud Platform.

Save