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About the Role

Machine Learning Engineers at Capital One will have the opportunity to be on the forefront of driving major AI transformations and scaling production models across the company. You will leverage cutting-edge open source frameworks, advanced algorithms, and emerging technologies to solve complex business problems in a fast-paced, collaborative, and inclusive environment.

Responsibilities

Design, build, and/or deliver ML models and components that solve real-world business problems, in collaboration with Product and Data Science teams.
Build and scale massive multi-tenant platforms for large footprint ML model training and/or serving.
Inform ML infrastructure decisions using understanding of ML modeling techniques and issues.
Solve complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment.
Collaborate as part of a cross-functional Agile team to create and enhance software for big data and ML applications.
Retrain, maintain, and monitor models in production.
Leverage or build cloud-based architectures, technologies, and/or platforms to deliver optimized ML models at scale.
Construct optimized data pipelines to feed ML models.
Leverage continuous integration and continuous deployment best practices, including test automation and monitoring, for successful deployment of ML models and application code.
Ensure code is well-managed to reduce vulnerabilities, models are well-governed from a risk perspective, and ML follows best practices in Responsible and Explainable AI.
Use programming languages like Python, Scala, or Java.

Requirements

Bachelor's Degree or higher in Computer Science, Machine Learning or a related quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Engineering).
At least 6 years of experience programming with Python, Java, Golang, or C++.
At least 6 years of Machine Learning experience using industry standard frameworks PyTorch or Tensorflow and libraries (Pandas, NumPy, Scikit-learn).
At least 6 years of experience using and operating large scale distributed systems (Spark, Ray) to prepare AI or Machine Learning data.
At least 4 years of experience deploying and operating Machine Learning solutions in production and operating production services in the cloud (AWS, GCP, Azure) and using Kubernetes to manage large scale containerized Machine Learning software systems.
Master's or Doctoral Degree in Computer Science, Electrical Engineering, Mathematics, or related field.
5+ years of experience optimizing ML algorithms, configurations, and infrastructure.
5+ years of experience following software development best practices including source control, testing, code reviews, CI/CD, etc.
5+ years of experience building resilient software solutions with pre-production testing, advanced deployment techniques, monitoring, alarms, and preparing incident response plans.
5+ years of experience working with Machine Learning techniques, model types, model architectures, training concepts, and how to evaluate model accuracy and diagnose and address common issues.
5+ years of experience designing, implementing, and scaling production-ready data pipelines for training and evaluating ML models.
ML industry impact through conference presentations, papers, blog posts, open source contributions, or patents.
Ability to communicate complex technical and machine learning concepts clearly to a variety of audiences.

Skills

Python
Java
Golang
C++
PyTorch
Tensorflow
Pandas
NumPy
Scikit-learn
Spark
Ray
AWS
GCP
Azure
Kubernetes
Supervised learning
Semi-supervised learning
Unsupervised learning
Reinforcement learning
Regression
Classification
Clustering
RNNs
CNNs
LSTMs
Transformers

Location

McLean, VA
San Francisco, CA

Work Type

Full-time

Experience Level

Senior Manager, IC
6 years
4 years
5+ years

Education Level

Bachelor's Degree in Computer Science, Machine Learning or a related quantitative field
Master's Degree in Computer Science, Electrical Engineering, Mathematics, or related field
Doctoral Degree in Computer Science, Electrical Engineering, Mathematics, or related field

Salary/Compensations

McLean, VA: $229,900 - $262,400
San Francisco, CA: $250,800 - $286,200

Benefits

Comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being.

About the Company

Capital One is a group of makers, breakers, doers and disruptors who love to solve real problems and meet real customer needs.
Capital One Financial is made up of several different entities.

Equal Opportunity

Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws.
Capital One promotes a drug-free workplace.
Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries.
If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1-800-304-9102 or via email at RecruitingAccommodation@capitalone.com.