Capital One

Financial Services

SeniorLeadMachineLearningEngineer(IntelligentFoundationsandExperiences)

$230–262k McLean, Virginia, United States FULL TIME
Market Sentiment
HIGH DEMAND

Neural analysis suggests this role is
optimal for Senior candidates.

The Brief

“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.

Financial Services
Problems you'll solve

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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