Senior Manager, Machine Learning Engineer

Capital One Financial

Confirmed live today High trust

Quick summary

Work type: On-site
Location: New York, NYSan Francisco, CAMcLean, VAPlano, TX
Salary: $229,900–$262,400 / yr
Employment: Full-time
Posted: 8 days ago
Freshness: Confirmed live today
Nearby: 99+ roles within 25 mi

Market check

Salary context

Competitive pay

How this pay compares to similar roles

Similar $226k

This role $246k

$174k $288k

below market most similar roles pay here above market

This role pays more than 65% of similar roles. Most pay $195,860–$257,012 — the blue band above. At the midpoint, this role pays about $246k versus about $226k 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 2107 open roles on FindRole.

Listed pay typically runs $197,300–$225,100 across 1107 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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The Senior Manager, Machine Learning Engineer (People Leader) 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 building massive multi-tenant platforms for large-footprint model training and serving. Key responsibilities include writing application code, automating deployments, constructing optimized data pipelines, and monitoring production models. The position requires proficiency in Python, Scala, Java, Golang, or C++, along with experience in PyTorch, Tensorflow, Pandas, NumPy, and Scikit-learn. Candidates must operate large-scale distributed systems using Spark or Ray and manage containerized software via Kubernetes on AWS, GCP, or Azure. The work focuses on solving complex business problems through responsible and explainable AI within an Agile framework.

Skills

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

What you'll do

Design, build, and deliver ML models and components to solve real-world business problems.
Build and scale massive multi-tenant platforms for large-footprint ML model training and serving.
Write and test application code to solve complex problems and automate deployment processes.
Retrain, maintain, and monitor ML models in production environments.
Construct optimized data pipelines to feed ML models and leverage cloud-based architectures.
Implement continuous integration and continuous deployment best practices including test automation.
Ensure all code and models follow best practices for Responsible and Explainable AI.
Recruit, nurture, and mentor engineering talent while providing hands-on technical leadership.

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, Pandas, NumPy, and Scikit-learn.
At least 6 years of experience using and operating large scale distributed systems like Spark or Ray.
At least 4 years of experience deploying and operating ML solutions in the cloud using Kubernetes.
At least 1 year of people leadership experience.
Master's or Doctoral Degree in Computer Science, Electrical Engineering, Mathematics, or a related field (preferred).
3+ years of experience managing and leading an ML engineering team (preferred).