Senior Machine Learning Engineer; Python, AWS, Big Data - Auto Loan Valuations & Insights

Senior Machine Learning Engineer (Python, AWS, Big Data) - Auto Loan Valuations & Insights at Capital One summary:

The Senior Machine Learning Engineer at Capital One develops, deploys, and maintains scalable machine learning models and infrastructure using Python, AWS, and big data technologies to support auto loan valuations and insights. The role involves collaboration within an Agile, cross-functional team including data scientists and engineers to deliver production-ready ML solutions. Responsibilities include model design, data pipeline construction, deployment automation, performance monitoring, and adherence to Responsible AI practices.

As a Capital One Machine Learning Engineer (MLE), you'll be part of an Agile team dedicated to product ionizing machine learning applications and systems ’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're currently seeking talented individuals to join our Valuations and Insights Team at Capital One Auto, a cross functional group for Business Analysts, Data Scientists, Data Engineers and Software Engineers, dedicated to building Machine Learning products to accurately assess Loan Valuations. This is a unique chance to build applications for both batch and real time use cases leveraging modern AWS infrastructure (EMR, Lambda) and Capital One Platforms.

If you're looking for an opportunity to contribute to a critical area of our business with a diverse and cutting-edge tech stack, we invite you to explore how your skills can make a real difference on our team.

What you’ll do in the role:

• The MLE role overlaps with many disciplines, such as Ops, Modeling, and Data Engineering. In this role, you'll be expected to perform many ML engineering activities, including one or more of the following:

• 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 4 years of experience programming with Python, Scala, or Java (Internship experience does not apply)

• 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 (scikit-learn, PyTorch, Dask, Spark, or Tensor Flow)

• At least 1 year of experience product ionizing, monitoring, and maintaining models

Preferred Qualifications:

• 1+ years of experience building, scaling, and optimizing ML…