Job Description
Center 1 (19052), United States of America, McLean, VirginiaLead Software Engineer, Back End (Python, PySpark, AWS)
Do you love building and pioneering in the technology space? Do you enjoy solving complex business problems in a fast-paced, collaborative, inclusive, and iterative delivery environment? At Capital One, 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 focus on machine learning architectural design, develop and review model and application code, and ensure 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. We are seeking Back End Software Engineers who are passionate about marrying data with emerging technologies. As a Capital One Software Engineer, you’ll have the opportunity to be on the forefront of driving a major transformation within Capital One.
What You’ll Do
- 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, including choice of model, data, and feature selection, model training, hyperparameter tuning, dimensionality, bias/variance, and validation.
- 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, including test automation and monitoring, to ensure successful deployment of ML models and application code.
- Ensure all code is well-managed to reduce vulnerabilities, models are well-governed from a risk perspective, and the ML follows best practices in Responsible and Explainable AI.
- Use programming languages like Python, Scala, or Java.
Basic Qualifications
- Bachelor’s Degree
- At least 6 years of professional software engineering experience (Internship experience does not apply)
- At least 1 year experience with cloud computing (AWS, Microsoft Azure, Google Cloud)
Preferred Qualifications
- Master's Degree
- 7+ years of experience in at least one of the following: Python, Scala, Java, Go, or Node.js
- 2+ years of experience with AWS, GCP, Azure, or another cloud service
- 4+ years of experience in open source frameworks
- 1+ years of people management experience
- 2+ years of experience in Agile practices
- 2+ years of experience with model development and deployment patterns