Lead Machine Learning Engineer, Enterprise Platforms

Salary: $215,200 - 245,600 per year Requirements:

• Bachelors degree
• Minimum 6 years of experience in designing and implementing data-heavy solutions using distributed computing (Internship experience is excluded)
• At least 4 years of experience with programming languages such as Python, Scala, or Java
• A minimum of 2 years of experience in developing, 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 constructing production-ready data pipelines for machine learning models (preferred)
• More than 3 years of hands-on experience with recognized machine learning frameworks such as scikit-learn, PyTorch, Dask, Spark, or TensorFlow (preferred)
• At least 2 years of experience in writing efficient, resilient, and maintainable code (preferred)
• More than 2 years of experience in data collection and preparation for machine learning models (preferred)
• Over 2 years of experience in a leadership position (preferred)
• A minimum of 1 year leading teams focused on developing machine learning solutions utilizing industry best practices, patterns, and automation (preferred)
• Experience in deploying machine learning solutions in cloud environments such as AWS, Azure, or Google Cloud Platform (preferred)
• Proven experience in designing, implementing, and scaling complex data pipelines for machine learning models and assessing their performance (preferred)
• Contribution to the machine learning field through conference presentations, papers, blog posts, open source contributions, or patents (preferred)

• Collaborate with multidisciplinary teams to design, develop, and deliver machine learning models and components addressing real-world business needs
• Utilize your knowledge of machine learning modeling techniques to inform infrastructure decisions including model selection, data usage, feature selection, training, hyperparameter optimization, dimensionality considerations, bias/variance analysis, and validation
• Tackle intricate challenges by writing and testing application code, and developing and validating machine learning models while automating tests and deployments
• Work as a part of a cross-functional Agile team to enhance software applications that facilitate advanced big data and machine learning functionalities
• Retrain, maintain, and monitor the performance of deployed models
• Implement cloud-based architectures and technologies to achieve scalable, optimized machine learning models
• Create efficient data pipelines to support machine learning model inputs
• Employ continuous integration and deployment practices, including test automation and monitoring, to guarantee successful model and application code deployment
• Ensure code management reduces vulnerabilities, and uphold governance of models from a risk standpoint while adhering to Responsible and Explainable AI principles
• Use programming languages such as Python, Scala, or Java effectively

• AI
• AWS
• Azure
• Big Data
• Cloud
• Support
• Java
• Machine Learning
• PyTorch
• Python
• Scala
• Spark
• TensorFlow

More:

At Capital One, we are seeking a Lead Machine Learning Engineer for our Enterprise Platforms Technology team. This Agile-focused role involves heavily influencing our technology solutions while ensuring production-scale application of machine learning. You will have the chance to engage in continuous learning, apply innovative techniques, and benefit from our comprehensive and inclusive health, financial, and wellness programs. Our work environment supports collaboration and empowers teams, making it vital for exceptional candidates to join us in delivering top-tier capabilities across the organization. We look forward to your application!

last updated 35 week of 2026