Distinguished Machine Learning Engineer

Capital One•McLean, VA

5d•$269,100 - $335,100

About The Position

Distinguished Machine Learning Engineer Overview As a Capital One Machine Learning Engineer, you'll be providing technical leadership to engineering teams dedicated to productionizing machine learning applications and systems at scale. You’ll participate in the detailed technical design, development, and implementation of machine learning applications using existing and emerging technology platforms. You’ll serve as a technical domain expert in machine learning, guiding machine learning architectural design decisions, developing and reviewing model and application code, and ensuring high availability and performance of our machine learning applications. You'll have the opportunity to continuously learn and apply the latest innovations and best practices in machine learning engineering. You’ll also mentor other engineers and further develop your technical knowledge and skills to keep Capital One at the cutting edge of technology. Team Description This role is part of the Risk Technology organization. In Risk Technology, we provide the foundation for Capital One to thrive in an uncertain world. Our engaged, empowered, and intelligent people produce outstanding products, working toward the common goal of transforming risk management with technology. We build data-driven tools that use machine learning to prevent risks & automatically detect issues before they impact our business, our customers, or our communities. In this role you will work with the Credit & Financial Risk Management teams to create real-time and intelligent risk management products that are powered by some of the advanced technology (such as Artificial Intelligence). In this role, you won't just execute a roadmap, you will be a strategist defining which modern technologies will solve problems our stakeholders haven’t even imagined yet. If you are ready to provide thought leadership and build engineering excellence across Capital One's engineering teams, come join us in our mission to change banking for good.

Requirements

Bachelor’s degree
At least 10 years of experience designing and building data-intensive solutions using distributed computing
At least 6 years of experience programming in C, C++, Python, or Scala
At least 3 years of experience with the full ML development lifecycle using modern technology in a business critical setting

Nice To Haves

Master's Degree
3+ years of experience designing, implementing, and scaling production-ready data pipelines that feed ML models
2+ years of experience using Dask, RAPIDS, or in High Performance Computing
2+ years of experience with the PyData ecosystem (NumPy, Pandas, and Scikit-learn)
Ability to communicate complex technical concepts clearly to a variety of audiences
ML industry impact through conference presentations, papers, blog posts, or open source contributions
Ability to attract and develop high-performing software engineers with an inspiring leadership style

Responsibilities

Deliver ML models and software components that solve challenging business problems in the financial services industry, working in collaboration with the Product, Architecture, Engineering, and Data Science teams
Drive the creation and evolution of ML models and software that enable state-of-the-art intelligent systems
Lead large-scale ML initiatives with the customer in mind
Leverage cloud-based architectures and technologies to deliver optimized ML models at scale
Optimize data pipelines to feed ML models
Use programming languages like Python, Scala, C/C++
Leverage compute technologies such as Dask and RAPIDS
Evangelize best practices in all aspects of the engineering and modeling lifecycles
Help recruit, nurture, and retain top engineering talent