Machine Learning Engineer 4 – Machine Learning Experiences

Capital One

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

Posted 10/23/2026full-timeUnited StatesMid-LevelSenior💰 $179,400 - $245,600 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in designing and deploying Machine Learning models and solutions, leveraging programming languages such as Python and Java, and utilizing cloud services like AWS, GCP, or Azure. Proficient in building optimized data pipelines and applying best practices in continuous integration and deployment.

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

KubernetesCI/CDCloud-Based ArchitecturesAutomated TestingMonitoring Tools

Certifications & Qualifications

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

Industry Keywords

Responsible AIExplainable AILarge-Scale Distributed SystemsProduction ModelsModel Evaluation

Tech Stack

Tools & technologies

AWSAzureCloudDistributed SystemsGoogle Cloud PlatformJavaKubernetesNumpyPandasPythonPyTorchRayScalaScikit-LearnSparkTensorflowC++Go

About the role

Key responsibilities & impact

Design, build, and 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 and issues
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 software
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 continuous integration and continuous deployment practices, including test automation and monitoring
Manage code to reduce vulnerabilities and govern models from a risk perspective
Follow Responsible and Explainable AI best practices
Use programming languages including Python, Scala, or Java

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, 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 and operating production cloud services using AWS, GCP, or Azure
At least 2 years of experience using Kubernetes to manage large-scale containerized Machine Learning software systems
Master's or Doctoral Degree in Computer Science, Electrical Engineering, Mathematics, or a related field (preferred)
Preferred experience optimizing ML algorithms, configurations, and infrastructure
Preferred experience with software development best practices, source control, testing, code reviews, and CI/CD
Preferred experience building resilient software solutions with pre-production testing, advanced deployment techniques, monitoring, alarms, and incident response plans
Preferred experience with Machine Learning techniques, model types, architectures, training concepts, and model evaluation
Preferred experience designing, implementing, and scaling production-ready data pipelines for training and evaluating ML models
Preferred experience as a technical lead developing ML solutions
Authored/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 provide 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
Equal opportunity employer committed to non-discrimination
Reasonable workplace accommodations
Drug-free workplace