Distinguished Machine Learning Engineer

Capital One • San Jose, CA

7d

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. 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

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

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Number of Employees: 5,001-10,000 employees