Lead Machine Learning Engineer – Manager IC

Capital One

Lead Machine Learning Engineer at Capital One, driving AI-powered solutions for banking. Collaborate across teams to develop and deploy innovative ML software and optimize data-driven tools.

Posted 6/9/2026full-timeCambridge • Massachusetts, Virginia • 🇺🇸 United StatesSenior💰 $179,400 - $225,100 per yearWebsite

ATS Keywords

Tailor your resume

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills

machine learninglarge language model inferencesimilarity searchmodel evaluationdata pipelinesPythonScalaJavaAI algorithmsML frameworks

Soft Skills

collaborationthought leadershiptechnical visionpeople leadershipcommunicationproblem-solvingorganizational skillsAgile methodologyrisk managementbest practices

Tools & Technologies

AWS BedrockGoogle CloudAzurescikit-learnPyTorchDaskSparkTensorFlowOpen Source AI technologiesinteractive AI tooling

Certifications & Qualifications

Bachelor's DegreeMaster's DegreeDoctoral Degree

Industry Keywords

AI-powered productsdata-intensive solutionsdistributed computingResponsible AIExplainable AIML infrastructuremodel governanceproduction-ready modelsRetrieval Augmented GenerationAI services at scale

Tech Stack

Tools & technologies

AWSAzureCloudJavaOpen SourcePythonPyTorchScalaScikit-LearnSparkTensorflow

About the role

Key responsibilities & impact

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

What you’ll need

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, Scala, or Java
At least 2 years of experience building, scaling, and optimizing ML systems
Master's or Doctoral Degree in computer science, electrical engineering, mathematics, or a similar field (Preferred)
7+ years of experience designing, developing, delivering, and supporting AI services at scale (Preferred)
3+ years of experience building production-ready data pipelines that feed ML models (Preferred)
3+ years of on-the-job experience with an industry recognized ML framework such as scikit-learn, PyTorch, Dask, Spark, or TensorFlow (Preferred)
3+ years of experience developing AI and ML algorithms or technologies using Python (Preferred)
2+ years of experience with Retrieval Augmented Generation (RAG) (Preferred)
2+ years of experience with data gathering and preparation for ML models (Preferred)
2+ years of people leader experience (Preferred)
1+ years of experience leading teams developing ML solutions using industry best practices, patterns, and automation (Preferred)
Experience designing, implementing, and scaling complex data pipelines for ML models and evaluating their performance (Preferred)
Experience leveraging interactive AI tooling to accelerate productivity, utilizing capabilities beyond basic code completion (Preferred)
Experience deploying scalable AI/ML solutions in a public cloud such as AWS Bedrock, Google Cloud, Azure (Preferred)

Benefits

Comp & perks

Performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI)
Comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being