Requirements

Must have:

• Bachelors Degree in a relevant field - Minimum 6 years of experience designing and implementing data-driven solutions using distributed computing (Internship experience not included) - At least 4 years of programming experience with Python, Scala, or Java - At least 2 years of experience in building, scaling, and optimizing machine learning systems - Masters or Doctoral Degree in computer science, electrical engineering, mathematics, or a related field (preferred) - Over 3 years of experience in creating production-grade data pipelines for ML models (preferred) - More than 3 years of hands-on experience with recognized ML frameworks such as scikit-learn, PyTorch, Dask, Spark, or TensorFlow (preferred) - At least 2 years of experience writing efficient, robust, and maintainable code (preferred) - Minimum 2 years of experience in data collection and preparation for ML models (preferred) - 2+ years of supervisory experience (preferred) - 1+ years leading teams in developing ML solutions utilizing industry best practices, patterns, and automation (preferred) - Experience deploying ML solutions in public cloud environments like AWS, Azure, or Google Cloud Platform (preferred) - Experience with designing, implementing, and scaling complex data pipelines for ML models while assessing their performance (preferred) - Contribution to the ML field through presentations, publications, blogs, open-source efforts, or patents (preferred)

Responsibilities

• Design, construct, and deliver machine learning models and components to address real-world business challenges in collaboration with Product and Data Science teams - Utilize your knowledge of machine learning modeling techniques and considerations to inform infrastructure decisions, including model selection, data handling, feature selection, training, and validation - Tackle complex issues by writing and testing application code, crafting and validating machine learning models, and automating testing and deployment processes - Work as part of a diverse Agile team to create and improve software for advanced big data and machine learning applications - Retrain, maintain, and supervise production models - Utilize or develop cloud-based architectures, technologies, and platforms for scalable machine learning models - Build efficient data pipelines to support machine learning models - Implement best practices in continuous integration and deployment, including test automation and monitoring for successful deployment of models and application code - Ensure code is securely managed, models are effectively governed from a risk management perspective, and that machine learning adheres to Responsible and Explainable AI practices - Employ programming languages, such as Python, Scala, or Java, in your work

Company

At Capital One, we are building a team of innovative machine learning engineers dedicated to delivering cutting-edge applications at scale. Our agile environment promotes learning and growth, enabling you to stay updated with the latest advancements and best practices in the machine learning domain. This role is located in McLean, VA, offering a competitive salary range of $197,300 to $225,100. Additionally, we provide a comprehensive suite of health, financial, and other benefits tailored for your well-being, with eligibility varying based on your employment status and management level. Join us in transforming technology in the banking sector!