Capital One Principal Associate Machine Learning Engineer 

India, Karnataka, Bengaluru 

973948306

Voyager (94001), India, Bangalore, Karnataka Principal Associate, Machine Learning Engineer

As a Capital One Machine Learning Engineer (MLE), you'll be part of a team focusing on automating governance within the model development lifecycle. You will work with model training and features and serving metadata at scale, to enable automated model governance decisions. You will contribute to building a system to do this for Capital One models, accelerating the move from fully trained models to deployable model artifacts ready to be used to fuel business decisioning.

What You’ll Do

• Work with model and platform teams to build systems that ingest large amounts of model and feature metadata that will feed into automated governance decisioning

• Partner with product and design teams to build elegant and scalable solutions to speed up governance processes

• Collaborate as part of a cross-functional Agile team to create and enhance software that enables state of the art, next generation big data and machine learning applications.

• Leverage cloud-based architectures and technologies to deliver optimized ML models at scale

• Construct optimized data pipelines to feed machine learning models.

• Use programming languages like Python, Scala, or Java

• Leverage continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployments of machine learning models and application code.

Basic Qualifications

• Bachelor’s Degree

• At least 4 years of experience designing and building data intensive solutions using distributed computing

• At least 3 years of experience programming with Python, Go, or Java

• At least 2 years of on-the-job experience with an industry recognized ML framework such as scikit-learn, PyTorch, Dask, Spark, or TensorFlow

• 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 developing performant, resilient, and maintainable code.

• Experience developing and deploying ML solutions in a public cloud such as AWS, Azure, or Google Cloud Platform

• Master’s Degree or PhD 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

• Authored/co-authored a paper on a ML technique, model, or proof of concept

• 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

If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1-800-304-9102 or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations.