Senior Manager, 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
Employment: Full-time
Posted: 4 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 $222k

This role $246k

$173k most similar roles pay here $280k

This role pays more than 68% of similar roles. Most pay $188,675–$254,750 — the shaded band above. At the midpoint, this role pays about $246k 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 1554 open roles on FindRole.

Listed pay typically runs $197,300–$225,100 across 796 roles with salary data.

Most-posted roles

View all roles at Capital One Financial

At a glance

TL;DR · Senior Manager, Machine Learning Engineer

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Senior Manager, Machine Learning Engineer will join a collaborative team to design, build, and deliver machine learning models and components that solve real-world business problems. The role involves building and scaling multi-tenant platforms for large-scale model training and serving, constructing optimized data pipelines, and managing the full lifecycle of production models including retraining, monitoring, and ensuring responsible AI practices. You will work within an Agile framework to develop software for big data applications while utilizing cloud-based architectures. Key technical requirements include proficiency in Python, Scala, or Java, along with experience in PyTorch, TensorFlow, Pandas, NumPy, and Scikit-learn. Additionally, the role requires expertise in distributed systems like Spark and Ray, as well as experience with Kubernetes and cloud platforms such as AWS, GCP, or Azure to manage containerized machine learning software at scale.

Skills

Python PyTorch TensorFlow Scikit-learn NumPy Pandas Kubernetes AWS GCP Azure Spark Ray Java Scala C++ CI/CD Data Pipelines Machine Learning

What you'll do

Design, build, and deliver machine learning models and components to solve real-world business problems.
Build and scale multi-tenant platforms for large-scale ML model training and serving.
Develop and validate application code while automating tests and deployment processes.
Construct optimized data pipelines to feed and support machine learning models.
Retrain, maintain, and monitor models in production environments.
Implement cloud-based architectures and technologies to deliver optimized models at scale.
Ensure all 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 6 years of experience programming with Python, Java, Golang, or C++.
At least 6 years of Machine Learning experience using PyTorch, TensorFlow, and libraries like Pandas, NumPy, and Scikit-learn.
At least 6 years of experience operating large scale distributed systems such as Spark or Ray to prepare AI/ML data.
At least 4 years of experience deploying ML solutions in production using cloud platforms (AWS, GCP, Azure) and Kubernetes.
Master's or doctoral degree in computer science, electrical engineering, mathematics, or a related field (preferred).
5+ years of experience optimizing ML algorithms, configurations, and infrastructure (preferred).
5+ years of experience following software development best practices including source control, testing, code reviews, and CI/CD (preferred).

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