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Capital One Distinguished Engineer Machine Learning United States, Virginia, Arlington 4538530
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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.
What you’ll do in the role:
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.
Basic Qualifications
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.
At least 2 years of experience using Dask, RAPIDS, or in High Performance Computing
At least 2 years of experience with the PyData ecosystem (NumPy, Pandas, and Scikit-learn)
Preferred Qualifications
Master's or doctoral degree in computer science, electrical engineering, mathematics, or a similar field.
3+ years of experience designing, implementing, and scaling production-ready data pipelines that feed ML models.
8+ years of experience within a large/data-intensive multi-line business environment.
Experience partnering with technology peers responsible for data architecture and distributed computing infrastructure/platforms.
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.
. Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level.
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 . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations.
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