Research Scientist (Machine Learning Engineer) 1139 views

At Capital One, they’re building a leading information-based technology company. Still founder-led by Chairman and Chief Executive Officer Richard Fairbank, Capital One is on a mission to help them customers succeed by bringing ingenuity, simplicity, and humanity to banking. They measure their efforts by the success their customers enjoy and the advocacy they exhibit. They are succeeding because they are succeeding.

Guided by their shared values, they thrive in an environment where collaboration and openness are valued. They believe that innovation is powered by perspective and that teamwork and respect for each other lead to superior results. They elevate each other and obsess about doing the right thing. Their associates serve with humility and deep respect for their responsibility in helping their customers achieve their goals and realize their dreams. Together, they are on a quest to change banking for good.

Research Scientist (Machine Learning Engineer)

Are you a high performing software engineer, data scientist or research scientist looking to take part in some of the most cutting edge research and production projects? Do you enjoy reading and investigating advancements in various applied machine learning architectures and solution white papers? Would you like to take part or drive the creation of publishable advancements in machine learning across various disciplines? You could be a great match for a Machine Learning Engineer (Research Scientist) role at Capital One’s Center for Machine Learning (C4ML).

As a Machine Learning Engineer (Research Scientist) in C4ML, you will contribute to building fast data and machine learning solutions to create and improve some of the most interesting use cases in the financial services industry. Capital One maintains a full stack of technology solutions including streaming big data, state of the art machine learning, micro-service architecture, distributed computation engines, and intuitive visualizations in the cloud. To manage this, they are working with several cutting-edge technologies and are actively developing and contributing to the open-source community. They are highly technical with strong backgrounds in their fields to support use cases ranging from cyber threat prevention to sophisticated NLP understanding in an always-on 24/7 service architecture. They have the highest executive support for acting as a catalyst for machine learning across Capital One providing their researchers with extraordinary diversity in topics.

What You Will Bring To The Role

• Excellent communication skills evidenced by multiple white papers (internal proprietary or externally published).
• Demonstrated ability to build full-stack systems architected for speed and distributed computing.
• Demonstrated ability to quickly learn new tools and paradigms to deploy cutting edge solutions.
• Experience mentoring junior engineers.
• Adept at simultaneously working on multiple projects, meeting deadlines, and managing expectations.

What You Will Do In The Role

• Act as an advisor to various lines of business to help create or improve projects.
• Develop both deployment architecture and scripts for automated system deployment in AWS.
• Code new machine learning paradigms, sometimes from first principles, for integration into production systems.
• Learn and work with subject matter experts to create large scale deployments using newly researched methodologies.
• Construct data staging layers and fast real-time systems to feed machine learning algorithms.
• Create white papers, attend conferences, and contribute to open-source software.

Basic Qualifications

• Bachelor’s Degree or Military Experience
• At least 2 years of experience designing and building full-stack solutions using distributed computing.
• At least 2 years of experience integrating with codebases.
• At least 2 years of experience working with Python, Scala, or Java.
• At least 2 years of experience with leading distributed file systems or multi-node database paradigms.

Preferred Qualifications

• Master’s Degree
• At least 2 years of research experience
• At least 4 years of experience in designing and building full-stack solutions using distributed computing.
• At least 6 years of experience integrating with codebases.
• At least 4 years working with Python, Scala, and Java.
• At least 4 years of experience with leading distributed file systems and multi-node database paradigms.
• At least 2 years leading teams in code development and balancing feature requests with feasibility constraints.
• A history of publications and conference attendance.