Senior Lead Machine Learning Engineer

Capital One Financial

Confirmed live today Low trust

Quick summary

Work type
On-site
Location
McLean, VA
Employment
Full-time
Posted
91 days ago
Freshness
Confirmed live today

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Salary context

How this pay compares to similar roles

Similar $225k
$168k $289k
below market most similar roles pay here above market

This listing doesn't post a salary. Most similar roles pay $195,150–$254,750.

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 · Senior Lead Machine Learning Engineer

The Sr Lead Machine Learning Engineer joins an Agile team dedicated to productionizing machine learning applications and systems at scale. In this role, you will participate in detailed technical design, develop and review model and application code, and ensure high availability and performance. You will build and deliver ML models that solve real-world business problems, construct optimized data pipelines, and automate tests and deployment. Key responsibilities include retraining, maintaining, and monitoring models in production while ensuring they follow best practices for Responsible and Explainable AI. You will utilize programming languages such as Python, Scala, or Java, along with frameworks like scikit-learn, PyTorch, Dask, Spark, or TensorFlow. The work involves building cloud-based architectures to deliver optimized models and managing data-intensive solutions using distributed computing.

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 automate tests and deployments for ML systems.
  • Retrain, maintain, and monitor machine learning models in production environments.
  • Construct optimized data pipelines to feed machine learning models.
  • Build and manage cloud-based architectures to deliver optimized ML models at scale.
  • Implement continuous integration and continuous deployment best practices for model deployment.
  • Ensure all code and models follow best practices for Responsible and Explainable AI.

What we're looking for

  • 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 (preferred).
  • Experience developing and deploying ML solutions in a public cloud such as AWS, Azure, or Google Cloud Platform (preferred).
  • 4+ years of experience with an industry recognized ML framework such as scikit-learn, PyTorch, Dask, Spark, or TensorFlow (preferred).

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