Capital One Machine Learning Engineer (MLE) will be part of an Agile team dedicated to productionizing machine learning applications and systems at scale. The role involves detailed technical design, development, and implementation of machine learning applications using existing and emerging technology platforms, focusing on architectural design, code review, and ensuring high availability and performance of ML applications.
Requirements
- At least 8 years of experience designing and building data-intensive solutions using distributed computing (Internship experience does not apply)
- At least 4 years of experience programming with Python, Scala, or Java
- At least 3 years of experience building, scaling, and optimizing ML systems
- At least 2 years of experience leading teams developing ML solutions
- Experience developing and deploying ML solutions in a public cloud such as AWS, Azure, or Google Cloud Platform
- 4+ years of on-the-job experience with an industry recognized ML framework such as scikit-learn, PyTorch, Dask, Spark, or TensorFlow
- 3+ years of experience developing performant, resilient, and maintainable code
Responsibilities
- 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.
Other
- Bachelor’s Degree
- 3+ years of people management experience
- ML industry impact through conference presentations, papers, blog posts, open source contributions, or patents
- Ability to communicate complex technical concepts clearly to a variety of audiences
- Capital One will consider sponsoring a new qualified applicant for employment authorization for this position.
