Machine Learning Engineer, Senior

Capital One

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

Posted 9/29/2026full-timeUnited StatesMid-LevelSenior💰 $197,300 - $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, 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 best practices for software development and ML operations.

Highest-signal resume keywords

Machine Learning Model DevelopmentCloud-Based Architecture (AWS, GCP, Azure)Large-Scale Distributed Systems (Spark, Ray)Continuous Integration and Continuous Deployment (CI/CD)Programming Languages (Python, Java, Golang, C++)

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Machine LearningModel EvaluationData Pipeline ConstructionFeature SelectionDimensionality ReductionBias/Variance AnalysisTest AutomationApplication Code WritingML Frameworks (PyTorch, TensorFlow)Data Manipulation (Pandas, NumPy, Scikit-learn)

Soft Skills

CollaborationProblem SolvingCommunicationAgile MethodologiesCross-Functional Teamwork

Tools & Technologies

KubernetesCloud Platforms (AWS, GCP, Azure)ML Infrastructure ToolsVersion Control SystemsMonitoring Tools

Industry Keywords

Responsible AIExplainable AIProduction ServicesSoftware Development Best PracticesModel Tuning

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 based on modeling techniques, data, feature selection, training, tuning, dimensionality, bias/variance, and validation
Write and test application code
Develop and validate ML models
Automate tests and deployment
Collaborate on a cross-functional Agile team to create and enhance big data and ML applications
Retrain, maintain, and monitor models in production
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
Ensure code is well-managed, models are risk-governed, and ML follows Responsible and Explainable AI best practices
Use programming languages such as 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, and Scikit-learn
At least 4 years of experience using and operating large-scale distributed systems such as Spark and Ray to prepare AI/ML 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 the cloud using AWS, GCP, or Azure
At least 2 years of experience using Kubernetes to manage large-scale containerized ML software systems
No new employment authorization sponsorship or immigration-related support available
Preferred: Master's or doctoral degree in computer science, electrical engineering, mathematics, or 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 Machine Learning techniques, model types, architectures, training concepts, and model evaluation
Preferred: 3+ years designing, implementing, and scaling production-ready data pipelines for training and evaluating ML models
Preferred: 1+ years as a technical lead developing ML solutions using industry best practices, patterns, and automation
Preferred: Authored/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 who require them