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Becoming Cloud-Ready With Capital One Programs
Here at Capital One, we understand that we can only be a tech-forward company innovating in the financial space if our associates are actively building their tech knowledge.
That’s why we have ensured our associates develop cloud-ready skills since we left our data centers behind and became an early adopter—among finance firms—of Amazon Web Services (AWS) to move to the public cloud. The agility, scalability and elasticity of the cloud are helping us build the bank of the future.
Our transition to the cloud pushed us to develop in-house training resources that help our associates learn, adapt and adopt new applicable skills. In other words, we encourage our associates to grow and continue to innovate alongside us. Learn about the programs below.
Tech College, which started in 2016, is our engineer-designed, and associate-led, learning platform with thousands of free courses for any associate interested in learning more about the latest technology disciplines.
Our engineers design and teach the curriculum so that it addresses the latest advancements and their practical, everyday use. Associates learn how we can use their new skills to enhance the experiences we’re developing for our customers. Topics include, but are not limited to, software engineering, mobile, machine learning, cybersecurity and cloud computing. A mix of self-guided and live courses are offered to accommodate various learning styles and schedules.
Capital One Developer Academy
We launched the Capital One Developer Academy (CODA) in 2017 to create a pathway into tech for non-computer science students from diverse backgrounds, majors, academic disciplines and experiences. The unique, intensive, six-month program prepares participants for a successful software engineering career at Capital One.
Machine Learning Engineering Training Program
The Machine Learning Engineering Training Program (MLETP) is a 160-hour program—approximately five months—designed for established software and data engineers with a focus on machine learning, artificial intelligence and data science. The skills-development program, which began in 2021, teaches the skills necessary to work in machine learning and AI.
MLETP is split between instructor-led content and classes students complete on their own time. Courses and topics focus on modeling, engineering and operations, industry and Capital One-specific tools, machine-learning workflows and data science. Scientists and engineers across Capital One’s machine-learning teams teach the courses and mentor students.
MLETP graduates can shift to a career in machine learning based on open job roles and discussions with their managers about career paths and goals.
Check out our Technology page to learn more about the available opportunities and how you too can help drive innovation.
Developing Cutting-Edge Skills With Tech College
Associates can enroll in Capital One’s Tech College, a learning platform that houses free courses for developing new tech skills.
Using Machine Learning to Change Banking for Good
Interested in learning how Capital One is building machine learning? Hear from Abhijit Bose on how we're developing in machine learning.
Ahead of the Curve: Working with an Innovative Tech Stack
For Usha, a career in computer science—and a passion for tech—allows her to innovate in her job, and give back to the next generation of coders. Usha uses advanced technology to solve real problems using automation.
- Lead Software Engineer, Devops (Remote- Eligible) R160706
- Senior Software Engineer, DevOps (Remote) R159696
- Director, Data Governance - Ontology and Data Modeling R161618
- Lead Data Engineer (Remote Eligible) R161662
- Senior Software Engineer, Back End (Remote) R154207
- Senior Data Engineer R161681
- Senior Software Engineer, Back End, Cloud Productivity (Remote-Eligible) R154244
- Lead Data Engineer (Remote Eligible) R161666
- Senior Software Engineer, Back End, Cloud Productivity (Remote-Eligible) R153244
- Senior Data Engineer (Remote) R159591