Senior Machine Learning Engineer - Enterprise Platforms

Salary: $229,900 - 286,200 per year Requirements:

• Bachelors degree
• Minimum of 8 years of experience in designing and implementing data-intensive solutions using distributed computing (Internship experience does not count)
• At least 4 years of experience programming in Python, Scala, or Java
• Minimum of 3 years of experience in developing, scaling, and optimizing machine learning systems
• At least 2 years of experience in leading teams that create machine learning solutions
• Masters or doctoral degree in computer science, electrical engineering, mathematics, or a related field (preferred)
• Experience with developing and deploying machine learning solutions in public cloud services such as AWS, Azure, or Google Cloud Platform (preferred)
• 4+ years of experience with an industry-recognized machine learning framework like scikit-learn, PyTorch, Dask, Spark, or TensorFlow (preferred)
• 3+ years of experience writing performant, resilient, and maintainable code (preferred)
• 3+ years of experience in data gathering and preparation for machine learning models (preferred)
• 3+ years of management experience (preferred)
• Contributions to the machine learning community through conference presentations, publications, blog posts, open source contributions, or patents (preferred)
• 3+ years of experience in building production-ready data pipelines that support machine learning models (preferred)
• Ability to articulate complex technical concepts to diverse audiences (preferred)

• Collaborate within an Agile team to design, develop, and implement machine learning applications at scale
• Create, build, and deliver machine learning models and components that address practical business challenges, working alongside Product and Data Science teams
• Make informed decisions regarding machine learning infrastructure based on understanding of modeling techniques, including model selection, data and feature selection, training, hyperparameter tuning, bias/variance, and validation
• Tackle intricate problems by writing and testing application code, developing and validating machine learning models, and automating tests and deployments
• Work with a cross-functional Agile team to enhance software that supports advanced big data and machine learning applications
• Monitor, maintain, and retrain models in production environments
• Utilize or build cloud-based architectures and technologies to optimize machine learning models at scale
• Develop optimized data pipelines to feed into machine learning models
• Apply best practices in continuous integration and continuous deployment, including test automation and monitoring, to ensure successful implementation of machine learning models and application code
• Ensure that all code is managed to minimize vulnerabilities, models are governed effectively from a risk standpoint, and machine learning conforms to best practices in Responsible and Explainable AI
• Use programming languages such as Python, Scala, or Java

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

More:

We are Capital Ones Enterprise Platforms Technology team which plays a vital role in establishing quality practices for developing technology solutions across the organization. Our focus is to deliver capabilities that embody these practices, while also offering an inclusive and competitive set of benefits that support your overall well-being. This is an excellent opportunity to join our forward-thinking team, where we value innovation and continuous learning in a collaborative environment.

last updated 32 week of 2026