Lead Machine Learning Engineer (Python, AWS, SQL, GenAI) (Enterprise Platforms Technology)

the opportunity to continuously learn and apply the latest innovations and best practices in machine learning engineering.

Team: The Marketing and Messaging team is responsible for delivering hyper-personalized messages and experiences that will delight the customer, attract prospects and drive increasing business value. The team builds scalable platforms that deliver omnichannel messages in owned and paid Adtech channels.

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.

- Bachelor's Degree - At least 6 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 2 years of experience building, scaling, and optimizing ML systems

- Master's or Doctoral Degree in computer science, electrical engineering, mathematics, or a similar field - 3+ years of experience building production-ready data pipelines that feed ML models - 3+ years of on-the-job experience with an industry recognized ML framework such as scikit-learn, PyTorch, Dask, Spark, or TensorFlow - 2+ years of experience developing performant, resilient, and maintainable code - 2+ years of experience with data gathering and preparation for ML models - 2+ years of people leader experience - 1+ years of experience leading teams developing ML solutions using industry best practices, patterns, and automation - Experience developing and deploying ML solutions in a public cloud such as AWS, Azure, or Google Cloud Platform - Experience designing, implementing, and scaling complex data pipelines for ML models and evaluating their performance - ML industry impact through conference presentations, papers, blog posts, open source contributions, or patents - Experience leveraging interactive AI tooling to accelerate productivity, utilizing capabilities beyond basic code completion

At this time, Capital One will not sponsor a new applicant for employment authorization, or offer any immigration related support for this position (i.e. H1B, F-1 OPT, F-1 STEM OPT, F-1 CPT, J-1, TN, E-2, E-3, L-1 and O-1, or any EADs or other forms of work authorization that require immigration support from an employer).

New York, NY: $215,200 - $245,600 for Lead Machine Learning Engineer