Sr. Staff Machine Learning Engineer
About the role
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.
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
Requirements
- Bachelor’s degree
- At least 10 years of experience designing and building data-intensive solutions using distributed computing
- At least 7 years of experience programming in C, C++, Python, or Scala
- At least 4 years of experience with the full ML development lifecycle using modern technology in a business critical setting
Qualifications
- Master's Degree
- 3+ years of experience designing, implementing, and scaling production-ready data pipelines that feed ML models
- 3+ years of experience using Dask, RAPIDS, or in High Performance