Lead ML Engineer, Production-Scale Systems

Capital One; Plano (TX); On-site; USD 286,000 - 327,000; Full time

Job summary

Capital One is seeking a Sr. Distinguished Machine Learning Engineer to provide technical leadership across productionizing ML applications at scale.

You will guide architectural decisions, review model and app code, and mentor engineers while delivering high-availability ML systems in collaboration with Product, Architecture, Engineering, and Data Science teams. You will work with Python/C/C++ among others, drive large-scale ML initiatives, optimize data pipelines, leverage cloud architectures,

Qualifications

• Bachelor’s degree required; 10+ years of data-intensive, distributed computing experience preferred.
• 7+ years programming in C, C++, Python, or Scala.
• 4+ years with ML development lifecycle in production/business-critical settings.
• Advanced knowledge of ML, data pipelines, and scalable architectures.

Responsibilities

• Deliver ML models and software components solving business problems in financial services.
• Drive creation and evolution of ML models and software for intelligent systems.
• Lead large-scale ML initiatives with customers in mind.
• Leverage cloud-based architectures to deliver optimized ML models at scale.
• Optimize data pipelines to feed ML models.
• Use Python, Scala, C/C++ in development.
• Leverage Dask and RAPIDS technologies.
• Advocate best practices across engineering and modeling lifecycles.
• Help recruit, nurture, and retain top engineering talent.

Skills

Python

C/C++

Distributed computing

ML engineering

Cloud computing

Scala

Education

Bachelor's degree

Master's degree

Tools

Dask

RAPIDS

PyData

Job description

Capital One is seeking a Sr. Distinguished Machine Learning Engineer to provide technical leadership across productionizing ML applications at scale.

You will guide architectural decisions, review model and app code, and mentor engineers while delivering high-availability ML systems in collaboration with Product, Architecture, Engineering, and Data Science teams. You will work with Python/C/C++ among others, drive large-scale ML initiatives, optimize data pipelines, leverage cloud architectures,