Job Description
As a Capital One Machine Learning Engineer (MLE), you'll be part of an Agile team 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 have the opportunity to continuously learn and apply the latest innovations and best practices in machine learning engineering.
What you’ll do in the role
- Design, build, and/or deliver ML models and components that solve real-world business problems, while working in collaboration with the Product and Data Science teams.
- Inform your ML infrastructure decisions using your understanding of ML modeling techniques and issues.
- Solve complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment.
- Collaborate as part of a cross-functional Agile team to create and enhance software that enables state-of-the-art big data and ML applications.
- Retrain, maintain, and monitor models in production.
- Leverage or build cloud-based architectures, technologies, and/or platforms to deliver optimized ML models at scale.
- Construct optimized data pipelines to feed ML models.
- Leverage continuous integration and continuous deployment best practices.
- Ensure all code is well-managed to reduce vulnerabilities and follows best practices in Responsible and Explainable AI.
- Use programming languages like Python, Scala, or Java.
Basic Qualifications
- Bachelor’s degree
- At least 4 years of experience programming with Python, Scala, or Java
- At least 3 years of experience designing and building data-intensive solutions using distributed computing
- At least 2 years of on-the-job experience with an industry recognized ML frameworks
- At least 1 year of experience productionizing, monitoring, and maintaining models
Preferred Qualifications
- 1+ years of experience building, scaling, and optimizing ML systems
- 1+ years of experience with data gathering and preparation for ML models
- 2+ years of experience with building models
- 2+ years of experience developing performant, resilient, and maintainable code
- Experience developing and deploying ML solutions in a public cloud
- Master's or doctoral degree in computer science, electrical engineering, mathematics, or a similar field
- 3+ years of experience with distributed file systems or multi-node database paradigms
- Contributed to open source ML software
- 3+ years of experience building production-ready data pipelines that feed ML models
- Experience designing, implementing, and scaling complex data pipelines for ML models and evaluating their performance
Salary Information
The minimum and maximum full-time annual salaries for this role are listed below, by location:
New York City (Hybrid On-Site): $165,100 - $188,500 for Senior Machine Learning Engineer
Candidates hired to work in other locations will be subject to the pay range associated with that location.
Application Information
This role is expected to accept applications for a minimum of 5 business days.
Equal Opportunity Employer
Capital One is an equal opportunity employer committed to diversity and inclusion in the workplace.
Contact Information
If you require an accommodation during the application process, please contact Capital One Recruiting at 1-800-304-9102 or via email at ***************@capitalone.com.
For technical support or questions about Capital One's recruiting process, please send an email to *******@capitalone.com.