Machine Learning Engineer

About The Company

Capital One is a financial services company where teams of makers, builders, and problem-solvers work together to address real customer needs. The company values collaborative, inclusive, and iterative delivery and applies technology to complex business challenges. Its machine learning teams use open-source frameworks, advanced algorithms, and cloud technologies to support AI initiatives and deliver solutions at scale.

About The Role

Capital One is seeking a Machine Learning Engineer 5 (IC) to design, develop, and operate production machine learning solutions. In this individual contributor role, you will work across disciplines including software engineering, data engineering, operations, and modeling. You will partner with Product and Data Science teams to build models and platforms that solve business problems, support large-scale training and inference, and advance the company’s AI capabilities.

The role is suited to an experienced engineer who can connect machine learning methods with reliable software and infrastructure. You will contribute throughout the model lifecycle, from data preparation and model development to deployment, monitoring, and ongoing improvement. This position is available in locations including McLean, Virginia; New York, New York; Richmond, Virginia; San Francisco, California; and San Jose, California. Capital One will consider sponsoring a qualified new applicant for employment authorization.

Qualifications

• Bachelor’s degree or higher in Computer Science, Machine Learning, or a related quantitative field such as Statistics, Economics, Operations Research, Analytics, Mathematics, or Engineering.
• At least 6 years of programming experience with Python, Java, Golang, or C++.
• At least 6 years of machine learning experience with industry-standard frameworks such as PyTorch or TensorFlow and libraries such as Pandas, NumPy, and scikit-learn.
• At least 6 years of experience using and operating large-scale distributed systems, such as Spark or Ray, to prepare AI and machine learning data.
• At least 4 years of experience deploying and operating production machine learning solutions and cloud services on AWS, GCP, or Azure, including Kubernetes-managed containerized systems.
• A master’s or doctoral degree in Computer Science, Electrical Engineering, Mathematics, or a related discipline is preferred.
• Preferred experience includes optimizing machine learning algorithms and infrastructure; software development practices such as source control, testing, code reviews, and CI/CD; and building resilient services with monitoring and incident response plans.
• Familiarity with machine learning methods, model architectures, training concepts, evaluation, and diagnosing issues such as underfitting and overfitting is preferred. Experience scaling production data pipelines, contributing to the field through publications or open-source work, and explaining technical concepts to varied audiences is also valued.
  
  

Responsibilities

• Design, build, and deliver machine learning models and software components in partnership with Product and Data Science teams.
• Develop and scale multi-tenant platforms for large-footprint model training and serving.
• Apply knowledge of model selection, features, training, tuning, dimensionality, bias and variance, and validation to inform infrastructure decisions.
• Write and test application code, develop and validate models, and automate testing and deployment.
• Work with cross-functional Agile teams to improve software supporting big data and machine learning applications.
• Build optimized data pipelines; leverage cloud architectures; and retrain, maintain, and monitor production models.
• Apply CI/CD, test automation, and monitoring practices to support successful deployments.
• Manage code and models responsibly, reduce vulnerabilities, support sound risk governance, and follow Responsible and Explainable AI practices.
  
  

Benefits

Indicative full-time annual salary ranges are $229,900–$262,400 in McLean; $209,000–$238,500 in Richmond; and $250,800–$286,200 in New York, San Francisco, and San Jose. Pay for other locations is based on the applicable local range. The actual salary offer is confirmed in the offer letter. This role may also be eligible for performance-based incentives, including cash bonuses and/or long-term incentives. Capital One offers a comprehensive benefits package supporting health, financial, and overall well-being. Eligibility varies by employment status and management level.

Equal Opportunity

Capital One is an equal opportunity employer committed to non-discrimination under applicable federal, state, and local laws, including protections for individuals with disabilities and veterans. The company promotes a drug-free workplace and considers qualified applicants with criminal histories in accordance with applicable laws. Reasonable accommodations are available during the recruiting process. Applications are expected to be accepted for at least five business days. No agencies, please.