Senior Manager, Machine Learning Engineering

Capital One Financial

Confirmed live today Low trust

Quick summary

Work type: On-site
Location: McLean, VANew York, NY
Employment: Full-time
Posted: 151 days ago
Freshness: Confirmed live today
Nearby: 99+ roles within 25 mi

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Salary context

How this pay compares to similar roles

Similar $231k

$174k $289k

below market most similar roles pay here above market

This listing doesn't post a salary. Most similar roles pay $201,250–$260,050.

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 Manager, Machine Learning Engineering

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The Senior Manager, Machine Learning Engineering joins an Agile team focused on productionizing machine learning applications and systems at scale. This role involves the technical design, development, and implementation of machine learning applications using existing and emerging technology platforms. Key responsibilities include building and delivering models to solve real-world business problems, constructing optimized data pipelines, and managing model retraining, monitoring, and deployment. The position requires developing and validating application code while ensuring high availability and performance. Candidates must 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, ensuring responsible and explainable AI, and managing distributed computing solutions to solve complex data-intensive problems.

Skills

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

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 solve complex problems and automate deployment processes.
Retrain, maintain, and monitor machine learning models in production environments.
Construct optimized data pipelines to feed machine learning models.
Build and leverage cloud-based architectures and technologies to deliver optimized models at scale.
Implement continuous integration and continuous deployment best practices, including test automation and monitoring.
Ensure all code and models follow best practices for Responsible and Explainable AI and risk governance.

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.
At least 4 years of people management experience.
Master's or Doctoral Degree in computer science, electrical engineering, mathematics, or a similar field (preferred).
4+ years of experience with an industry recognized ML framework such as scikit-learn, PyTorch, Dask, Spark, or TensorFlow (preferred).