Machine Learning Engineer

Capital One

. Design, build, and deliver machine learning 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

Use this summary to align your resume positioning with the role.

Demonstrates expertise in designing and deploying machine learning models, leveraging cloud-based architectures and large-scale distributed systems. Proficient in programming with Python and Java, and experienced in applying CI/CD practices for model deployment and monitoring.

Highest-signal resume keywords

Machine Learning ExperiencePython ProgrammingAWS Cloud ServicesCI/CD PracticesData Pipeline Development

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 LearningPythonJavaPyTorchTensorFlowPandasNumPyScikit-learnSparkKubernetes

Soft Skills

CollaborationProblem SolvingCommunicationAgile Methodologies

Tools & Technologies

AWSGCPAzureCI/CD ToolsMonitoring Tools

Certifications & Qualifications

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

Industry Keywords

Machine Learning ModelsBig Data ApplicationsResponsible AIExplainable AIProduction Services

Tech Stack

Tools & technologies

AWSAzureCloudDistributed SystemsGoogle Cloud PlatformJavaKubernetesNumpyPandasPythonPyTorchRayScalaScikit-LearnSparkTensorflowC++Go

About the role

Key responsibilities & impact

Design, build, and deliver machine learning 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, feature selection, training, tuning, dimensionality, bias/variance, and validation
Write and test application code, develop and validate ML models, and automate testing and deployment
Collaborate on 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, test automation, and monitoring practices for model and application deployment
Manage code to reduce vulnerabilities and govern models from a risk perspective using Responsible and Explainable AI best practices
Use programming languages including Python, Scala, or Java
Join Capital One's Dealer Tech division, developing secure technology that streamlines auto financing for dealers

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 programming experience with Python, Java, Golang, or C++
At least 4 years of Machine Learning experience using PyTorch or TensorFlow and Pandas, NumPy, or Scikit-learn
At least 4 years of experience using and operating large-scale distributed systems such as Spark or Ray to prepare AI or Machine Learning data
At least 2 years of experience deploying and operating Machine Learning solutions in production
At least 2 years of experience operating production services in AWS, GCP, or Azure and using Kubernetes to manage large-scale containerized Machine Learning software systems
No employer-sponsored employment authorization or immigration-related support available for new applicants
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
Preferred: Authored or co-authored a paper on an ML technique, model, or proof of concept

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 accommodations for applicants with disabilities