Machine Learning Engineer

Capital One

. Design, build, and/or deliver ML models and components solving real-world business problems .

Posted 9/22/2026full-timeUnited StatesMid-LevelSenior💰 $179,400 - $225,100 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in designing and deploying Machine Learning models and solutions, with a strong focus on cloud-based architectures and large-scale distributed systems. Proficient in programming languages such as Python and Java, and experienced in applying CI/CD best practices for optimized ML operations.

Highest-signal resume keywords

Machine Learning ExperiencePython ProgrammingCloud Services (AWS, GCP, Azure)Kubernetes ManagementData Pipeline Development

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Machine LearningPythonJavaPyTorchTensorFlowPandasNumPyScikit-learnSparkRay

Soft Skills

CollaborationProblem SolvingCommunicationAgile Methodologies

Tools & Technologies

AWSGCPAzureKubernetesCI/CD

Certifications & Qualifications

Bachelor's Degree in Computer ScienceMaster's or Doctoral Degree (Preferred)

Industry Keywords

Machine Learning ModelsData ScienceBig Data ApplicationsResponsible AIExplainable AI

Tech Stack

Tools & technologies

AWSAzureCloudDistributed SystemsGoogle Cloud PlatformJavaKubernetesNumpyPandasPythonPyTorchRayScalaScikit-LearnSparkTensorflowC++Go

About the role

Key responsibilities & impact

Design, build, and/or deliver ML models and components solving real-world business problems
Collaborate with Product and Data Science teams
Inform ML infrastructure decisions using knowledge of modeling techniques, data and feature selection, training, tuning, dimensionality, bias/variance, and validation
Write and test application code; develop and validate ML models; automate testing and deployment
Collaborate in cross-functional Agile teams to create and enhance big data and ML applications
Retrain, maintain, and monitor production models
Leverage or build cloud-based architectures, technologies, and platforms to deliver optimized ML models at scale
Construct optimized data pipelines feeding ML models
Apply CI/CD best practices, including test automation and monitoring
Ensure code is well-managed, models are governed from a risk perspective, and ML follows Responsible and Explainable AI best practices
Use programming languages such as Python, Scala, or Java
Work with the GRC team and partners across Capital One to build and deploy AI-powered risk management solutions

Requirements

What you’ll need

Bachelor's Degree or higher in Computer Science, Machine Learning, or a related quantitative field
At least 4 years of experience programming with Python, Java, Golang, or C++
At least 4 years of Machine Learning experience using PyTorch or TensorFlow and Pandas, NumPy, and Scikit-learn
At least 4 years of experience using and operating large-scale distributed systems such as Spark or Ray to prepare AI/ML data
At least 2 years of experience deploying and operating Machine Learning solutions in production and operating production cloud services using AWS, GCP, or Azure
At least 2 years of experience using Kubernetes to manage large-scale containerized ML software systems
Preferred: Master's or doctoral degree in a related field
Preferred: 3+ years optimizing ML algorithms, configurations, and infrastructure
Preferred: 3+ years following software development best practices, including source control, testing, code reviews, and CI/CD
Preferred: 3+ years building resilient software solutions with pre-production testing, advanced deployment techniques, monitoring, alarms, and incident response plans
Preferred: 3+ years working with ML techniques, model types, architectures, training concepts, and model evaluation
Preferred: 3+ years designing, implementing, and scaling production-ready data pipelines
Preferred: 1+ year as a technical lead developing ML solutions
Authored or co-authored a paper on an ML technique, model, or proof of concept
Capital One will not sponsor a new applicant for employment authorization or offer immigration-related support for this position

Benefits

Comp & perks

Performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI)
Comprehensive, competitive, and inclusive health, financial and other benefits supporting total well-being
Reasonable accommodation support
Equal opportunity and non-discrimination protections