Senior Machine Learning Engineer (GenAI, Python)

Requirements

Must have:

- Bachelors Degree - Minimum of 8 years in designing and building data-intensive solutions using distributed computing (Internship experience does not qualify) - At least 4 years of programming experience with Python, Scala, or Java - Minimum of 3 years in building, scaling, and optimizing machine learning systems - At least 2 years of experience in leading teams developing machine learning solutions - Masters or doctoral degree in computer science, electrical engineering, mathematics, or a related field (preferred) - Experience in developing and deploying machine learning solutions on public clouds like AWS, Azure, or Google Cloud Platform (preferred) - Over 4 years of practical experience with an industry-recognized machine learning framework such as scikit-learn, PyTorch, Dask, Spark, or TensorFlow (preferred) - 3+ years of experience writing efficient, resilient, and maintainable code (preferred) - 3+ years of experience with data gathering and preparation for machine learning models (preferred) - Experience in people management for 3+ years (preferred) - Track record of industry influence through conference presentations, papers, blogs, open-source contributions, or patents (preferred) - 3+ years in building production-ready data pipelines that feed machine learning models (preferred) - Strong ability to convey complex technical concepts clearly to diverse audiences (preferred)

Responsibilities:

- Design, build, and deliver machine learning models and components to address real-world business challenges while collaborating with Product and Data Science teams. - Utilize your knowledge of machine learning modeling techniques to inform decisions on infrastructure, including model selection, data and feature choices, model training, hyperparameter tuning, dimensionality reduction, bias/variance, and validation. - Tackle complex issues by writing and testing application code, developing and validating machine learning models, and facilitating automation of tests and deployment. - Work collaboratively as part of a cross-functional Agile team to create and enhance software that supports state-of-the-art big data and machine learning applications. - Maintain, monitor, and retrain models that are in production. - Utilize or develop cloud-based architectures and technologies to deliver optimized machine learning models quickly at scale. - Construct efficient data pipelines to support machine learning models. - Implement continuous integration and deployment best practices, including test automation and monitoring, to guarantee successful rollout of machine learning models and application code. - Ensure code management practices are in place to minimize vulnerabilities, models are governed from a risk perspective, and machine learning operations adhere to best practices in Responsible and Explainable AI. - Use programming languages such as Python, Scala, or Java to perform the above tasks.

Company:

At Capital One, we are seeking a Senior Lead Machine Learning Engineer to join our Agile team dedicated to bringing machine learning applications to life at scale. We focus on the technical design, development, and implementation of innovative solutions leveraging cutting-edge technology platforms. Were committed to continuous learning and applying the latest advancements and best practices in machine learning engineering. This role is based in our offices located in Cambridge, MA; McLean, VA; or Richmond, VA, and offers a comprehensive, competitive benefits package that supports overall well-being. We also promote an inclusive workplace, actively seeking diverse perspectives and backgrounds.