Capital One
Financial Services
SeniorLeadMachineLearningEngineer(IntelligentFoundationsandExperiences)
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“Senior Lead Machine Learning Engineer (Intelligent Foundations and Experiences) at Capital One. Skills: Machine Learning Engineering, AI/ML capabilities, LLM inference, Agentic AI. Lead pods of engineers. Build AI/ML capabilities”
Industry & Context.
Solve complex problems
What They're Looking For.
Must Have
Bachelor's Degree, 8+ years data-intensive solutions, 4+ years Python, Scala, or Java, 3+ years ML systems, 2+ years leading ML teams
Nice to Have
Master's Degree, 6+ years AI services at scale, 3+ years AI/ML algorithms (Python), 2+ years Retrieval Augmented Generation, Experience with ML research, Deploying AI/ML in public cloud, Designing complex data pipelines
What You'll Do.
Lead pods of engineers
Build AI/ML capabilities
Design AI-powered products
Build AI-powered components
Leverage LLM inference
Leverage similarity search
Collaborate with cross-functional team
Develop AI-powered products
Scale AI-powered products
Inform ML infrastructure decisions
Write and test application code
Retrain models in production
Maintain models in production
Monitor models in production
Build cloud-based architectures
Build cloud technologies
Build cloud platforms
Deliver optimized ML models
Construct data pipelines
Leverage CI/CD best practices
Ensure successful deployment
Reduce vulnerabilities
Follow Responsible AI
Follow Explainable AI
How You'll Work.
Team & Collaboration
Agile team; Cross-functional team; Product and Data Science environment
Process & Methodology
Agile
Full Job Description
Senior Lead Machine Learning Engineer (Intelligent Foundations and Experiences) As a Capital One **Machine Learning Engineer (MLE)** , you'll be part of an Agile team dedicated to productionizing machine learning applications and systems at scale. You’ll participate in the detailed technical design, development, and implementation of machine learning applications using existing and emerging technology platforms. You’ll focus on machine learning architectural design, develop and review model and application code, and ensure high availability and performance of our machine learning applications. You'll have the opportunity to continuously learn and apply the latest innovations and best practices in machine learning engineering. ****What you’ll do in the role:**** The MLE role overlaps with many disciplines, such as Ops, Modeling, and Data Engineering. In this role, you'll be expected to perform many ML engineering activities, including one or more of the following: * Lead dedicated pods of software, data and machine learning engineers in building AI/ML capabilities for Credit and Financial Risk Management products, serving as a technical mentor to the team on these core technologies * Design, build, and deliver AI-powered products and components that solve real-world business problems, leveraging expertise in model experimentation, LLM inference, similarity search, and agentic AI within a collaborative Product and Data Science environment * Collaborate with a cross-functional team of engineers, data scientists, and designers to develop and scale AI-powered products that enable optimized associate performance and deliver world-class customer value * Inform your ML infrastructure decisions using your understanding of ML modeling techniques and issues, including choice of model, data, and feature selection, model training, hyperparameter tuning, dimensionality, bias/variance, and validation) * Solve complex problems by writing and testing application code, developing and
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