Senior Lead Machine Learning Engineer

Capital One Financial

Confirmed live yesterday Low trust

Quick summary

Work type: On-site
Location: McLean, VA
Salary: $229,900–$262,400 / yr
Posted: 45 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 $224k

This role $246k

$174k most similar roles pay here $285k

This role pays more than 67% of similar roles. Most pay $194,125–$254,750 — the shaded band above. At the midpoint, this role pays about $246k versus about $224k 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 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. To succeed, you must utilize programming languages such as Python, Scala, or Java, alongside frameworks like scikit-learn, PyTorch, Dask, Spark, or TensorFlow. You will also leverage cloud-based architectures to deliver models while adhering to best practices for Responsible and Explainable AI. This role addresses the technical challenge of scaling big data and machine learning applications within a complex production environment.

Skills

Machine Learning Python Scala Java PyTorch TensorFlow scikit-learn Spark 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 high-quality application code using Python, Scala, or Java.
Construct optimized data pipelines to feed machine learning models.
Build and manage cloud-based architectures to deliver optimized ML models at scale.
Retrain, maintain, and monitor machine learning models in production environments.
Implement CI/CD best practices, including test automation and monitoring, for model deployment.
Ensure all models follow best practices in Responsible and Explainable AI.
Inform infrastructure decisions based on knowledge of modeling techniques like hyperparameter tuning and feature selection.

What we're looking for

Bachelor's Degree in a relevant field.
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.
Master's or Doctoral Degree in computer science, electrical engineering, mathematics, or a similar field.
Experience deploying ML solutions in public clouds like AWS, Azure, or Google Cloud Platform.
4+ years of experience with industry-recognized ML frameworks such as scikit-learn, PyTorch, Dask, Spark, or TensorFlow.

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