Director, Machine Learning Engineer

Capital One Financial

Confirmed live yesterday High trust

Quick summary

Work type: On-site
Location: McLean, VA
Salary: $269,100–$307,200 / yr
Employment: Full-time
Posted: 5 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 $232k

This role $288k

$169k $322k

below market most similar roles pay here above market

This role pays more than 89% of similar roles. Most pay $202,800–$262,112 — the blue band above. At the midpoint, this role pays about $288k versus about $232k 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.

Most-posted roles

View all roles at Capital One Financial

At a glance

TL;DR · Director, Machine Learning Engineer

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The Director, Machine Learning Engineer joins a collaborative team to drive major AI transformations and scale production models within the financial services industry. This role involves delivering ML models and software components that solve complex business problems while leading large-scale initiatives. Key responsibilities include optimizing data pipelines, evangelizing engineering best practices, and mentoring engineering talent. The successful candidate will utilize programming languages such as Python, Scala, Java, Golang, or C++ to build intelligent systems. Technical requirements include proficiency with PyTorch, Tensorflow, Pandas, NumPy, and Scikit-learn. Additionally, the role requires experience with distributed systems like Spark and Ray, as well as cloud platforms including AWS, GCP, and Azure, using Kubernetes to manage large-scale containerized machine learning software systems for production environments.

Skills

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

What you'll do

Deliver ML models and software components to solve complex business problems in financial services.
Drive the creation and evolution of ML models that enable state-of-the-art intelligent systems.
Lead large-scale ML initiatives using cloud-based architectures to deliver optimized models at scale.
Optimize data pipelines to feed machine learning models.
Evangelize best practices across all aspects of the engineering and modeling lifecycles.
Recruit, nurture, and retain top engineering talent.
Mentor peers and junior engineers while providing deep, hands-on technical contributions.

What we're looking for

Bachelor's Degree or higher in Computer Science, Machine Learning, or a related quantitative field.
At least 3 years of people leadership experience.
At least 8 years of experience programming with Python, Java, Golang, or C++.
At least 6 years of Machine Learning experience using PyTorch or Tensorflow and libraries like Pandas, NumPy, and Scikit-learn.
At least 6 years of experience using and operating large scale distributed systems like Spark or Ray to prepare AI data.
At least 5 years of experience deploying and operating ML solutions in the cloud (AWS, GCP, Azure) using Kubernetes.
Master's or Doctoral Degree in Computer Science, Electrical Engineering, Mathematics, or a related field (preferred).
5+ years of experience managing and leading an engineering team (preferred).