Machine Learning Engineer 4 (Manager)

Capital One Financial

Confirmed live yesterday High trust

Quick summary

Work type: On-site
Location: New York, NYMcLean, VA
Salary: $197,300–$225,100 / yr
Employment: Full-time
Posted: 6 days ago
Freshness: Confirmed live yesterday
Nearby: 99+ roles within 25 mi

Market check

Salary context

Competitive pay

How this pay compares to similar roles

Similar $222k

This role $211k

$177k $253k

below market most similar roles pay here above market

This role pays more than 52% of similar roles. Most pay $200,206–$243,600 — the blue band above. At the midpoint, this role pays about $211k versus about $222k 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 1917 open roles on FindRole.

Listed pay typically runs $197,300–$225,100 across 1045 roles with salary data.

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View all roles at Capital One Financial

At a glance

TL;DR · Machine Learning Engineer 4 (Manager)

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The Machine Learning Engineer 4 (Manager, IC) joins a collaborative team to drive major AI transformations and scale production models. This role involves designing, building, and delivering machine learning models and components to solve real-world business problems while collaborating with Product and Data Science teams. Key responsibilities include writing and testing application code, automating deployments, constructing optimized data pipelines, and monitoring models in production. The position requires expertise in Python, Scala, Java, Golang, or C++, alongside frameworks like PyTorch, Tensorflow, Pandas, NumPy, and Scikit-learn. Candidates must operate large-scale distributed systems using Spark and Ray, manage containerized software via Kubernetes, and utilize cloud platforms like AWS, GCP, or Azure. The work focuses on implementing Responsible and Explainable AI within a production environment.

Skills

Python PyTorch TensorFlow Spark Ray Kubernetes AWS GCP Azure Scala Java Golang C++ Pandas NumPy Scikit-learn CI/CD Data Pipelines Transformers RNNs CNNs LSTMs

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.
Construct and optimize data pipelines to feed machine learning models.
Retrain, maintain, and monitor machine learning models in production environments.
Build and leverage cloud-based architectures 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.

What we're looking for

Bachelor's Degree or higher in Computer Science, Machine Learning, or a related quantitative field.
At least 4 years of experience programming with Python, Java, Golang, or C++.
At least 4 years of Machine Learning experience using PyTorch or Tensorflow and libraries like Pandas, NumPy, and Scikit-learn.
At least 4 years of experience using and operating large scale distributed systems like Spark or Ray to prepare AI or ML data.
At least 2 years of experience deploying and operating ML solutions in production using cloud services (AWS, GCP, Azure) and Kubernetes.
Master's or Doctoral Degree in Computer Science, Electrical Engineering, Mathematics, or a related field (preferred).
3+ years of experience optimizing ML algorithms, configurations, and infrastructure (preferred).
3+ years of experience following software development best practices including source control, testing, code reviews, and CI/CD (preferred).

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