Senior Staff Machine Learning Engineer

Capital One

. Deliver ML models and software components solving challenging business problems in the financial services industry .

Posted 9/29/2026full-timeUnited StatesSenior💰 $314,800 - $359,300 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in delivering and optimizing machine learning models and software solutions within the financial services industry, leveraging cloud technologies and large-scale distributed systems. Proven ability to lead initiatives, communicate complex concepts, and develop high-performing engineering teams.

Highest-signal resume keywords

Machine Learning ExperiencePython ProgrammingCloud Services (AWS, GCP, Azure)Kubernetes ManagementLarge Scale Distributed Systems (Spark, Ray)

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Machine LearningPythonJavaGolangPyTorchTensorFlowPandasNumPyScikit-learnData Pipeline Optimization

Soft Skills

LeadershipCommunicationCollaborationMentoringStrategic Thinking

Tools & Technologies

KubernetesDaskRAPIDSAWSGCPAzureSparkRay

Certifications & Qualifications

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

Industry Keywords

Financial ServicesMachine Learning StrategyProduction ServicesIntelligent SystemsEngineering Best Practices

Tech Stack

Tools & technologies

AWSAzureCloudDistributed SystemsGoogle Cloud PlatformJavaKubernetesNumpyOpen SourcePandasPythonPyTorchRayScalaScikit-LearnSparkTensorflowC++Go

About the role

Key responsibilities & impact

Deliver ML models and software components solving challenging business problems in the financial services industry
Collaborate with Product, Architecture, Engineering, and Data Science teams
Drive creation and evolution of ML models and software enabling state-of-the-art intelligent systems
Lead large-scale ML initiatives with the customer in mind
Leverage cloud-based architectures and technologies to deliver optimized ML models at scale
Optimize data pipelines to feed ML models
Use programming languages such as Python, Scala, Java, and GoLang
Leverage compute technologies such as Dask and RAPIDS
Evangelize best practices across engineering and modeling lifecycles
Help recruit, nurture, and retain top engineering talent

Requirements

What you’ll need

Bachelor's Degree or higher in Computer Science, Machine Learning or a related quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Engineering)
At least 10 years of experience programming with Python, Java, Golang, or C++
At least 8 years of Machine Learning experience using PyTorch or Tensorflow and libraries including Pandas, NumPy, and Scikit-learn
At least 8 years of experience using and operating large scale distributed systems such as Spark and Ray to prepare AI or Machine Learning data
At least 8 years of experience deploying and operating Machine Learning solutions in production and operating production services in the cloud (AWS, GCP, Azure)
At least 8 years of experience using Kubernetes to manage large scale containerized Machine Learning software systems
Preferred: Master's or Doctoral Degree in Computer Science, Electrical Engineering, Mathematics, or related field
Preferred: 5+ years of experience architecting and designing resilient, large-scale, production machine learning systems
Preferred: 7+ years of experience optimizing ML algorithms, configurations, and infrastructure
Preferred: 7+ years of experience with Machine Learning techniques, model types, architectures, training concepts, and model evaluation
Preferred: 9+ years of experience designing, implementing, and scaling production-ready data pipelines for training and evaluating ML models
Experience shaping long term cross-organizational machine learning strategy
Ability to communicate complex technical concepts clearly to executive leadership
Recognized ML industry leadership through conference presentations, papers, blog posts, open source contributions, or patents
Experience developing high-performing ML engineers with an inspiring leadership style
Capital One will consider sponsoring a new qualified applicant for employment authorization 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 accommodations for qualified applicants with disabilities