Senior Lead Machine Learning Engineer

Capital One Financial

Confirmed live yesterday High trust

Quick summary

Work type
On-site
Location
McLean, VASan Francisco, CACambridge, MASan Jose, CANew York, NY
Salary
$229,900–$262,400 / yr
Posted
7 days ago
Freshness
Confirmed live yesterday

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 $195,787–$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

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 in cloud-based architectures and frameworks such as scikit-learn, PyTorch, Dask, Spark, or TensorFlow. You will solve complex problems by writing application code, automating tests, and managing robust deployment pipelines.

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.
  • Retrain, maintain, and monitor machine learning models in production environments.
  • Build and manage cloud-based architectures to deliver optimized ML models at scale.
  • 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 modeling techniques like hyperparameter tuning and feature selection.

What we're looking for

  • Bachelor's degree required; Master's or Doctoral degrees in relevant fields are 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 machine learning systems.
  • At least 2 years of experience leading teams developing machine learning 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 developing performant code and building production-ready data pipelines.
  • Experience deploying ML solutions in public clouds such as AWS, Azure, or Google Cloud Platform.

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