Lead Machine Learning Engineer developing AI-powered solutions to transform risk management at Capital One. Collaborating with cross-functional teams to deliver innovative products using advanced machine learning techniques.
Responsibilities
Partner with a cross-functional team of engineers, data scientists, product managers, and designers to deliver AI-powered products that change how our associates work and provide value to our customers.
Design, develop, test, deploy, and support AI software components utilizing machine learning models, including model evaluation and experimentation, large language model inference, similarity search, guardrails, governance, observability and agentic AI.
Fine-tune, develop and evaluate machine learning and foundation models.
Collaborate as part of a cross-functional Agile team to create and enhance software that utilizes state-of-the-art AI and ML capabilities.
Contribute thought leadership and technical vision to the long term roadmap of pioneering AI systems at Capital One.
Leverage a broad stack of Open Source and SaaS AI technologies.
Inform your ML infrastructure decisions using your understanding of ML modeling techniques and issues.
Retrain, maintain, and monitor models in production.
Construct optimized data pipelines to feed ML models.
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.
Requirements
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, Go, Scala, or Java
At least 3 years of experience deploying scalable software solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud)
Benefits
comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being
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