Machine Learning Engineer - Foundations (MLX)

Requirements:

• Bachelors 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 4 years of programming experience with Python, Java, Golang, or C++.
• At least 4 years of Machine Learning experience with PyTorch or TensorFlow and libraries such as Pandas, NumPy, and Scikit-learn.
• At least 4 years of experience 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, running cloud production services (AWS, GCP, or Azure), and using Kubernetes to manage large-scale containerized Machine Learning systems.
• Preferred: Masters or doctoral degree in Computer Science, Electrical Engineering, Mathematics, or a related field.
• Preferred: 3+ years of experience optimizing ML algorithms, configurations, and infrastructure.
• Preferred: 3+ years of experience with software development best practices, including source control, testing, code reviews, and CI/CD.
• Preferred: 3+ years of experience building resilient software with pre-production testing, advanced deployment techniques, monitoring, alarms, and incident response planning.
• Preferred: 3+ years of experience with Machine Learning techniques, model types and architectures, training concepts, and evaluating model accuracy and diagnosing issues such as underfitting and overfitting.
• Preferred: 3+ years of experience designing, implementing, and scaling production-ready data pipelines for training and evaluating ML models.
• Preferred: 1+ year of experience as a technical lead developing ML solutions using industry best practices, patterns, and automation.
• Preferred: Authored or co-authored a paper on an ML technique, model, or proof of concept.
• Capital One will not sponsor new employment authorization or provide immigration-related support for this position.

Responsibilities:

• Design and deliver ML models and components to address real-world business problems in partnership with Product and Data Science teams.
• Apply knowledge of modeling techniques and challenges to inform ML infrastructure decisions, including model, data, and feature selection, training, tuning, dimensionality, bias and variance, and validation.
• Write and test application code, develop and validate ML models, and automate testing and deployment to solve complex problems.
• Work with a cross-functional Agile team to build and improve software supporting advanced big data and ML applications.
• Retrain, maintain, and monitor models in production.
• Use or build cloud architectures, technologies, and platforms to deliver optimized ML models at scale.
• Build optimized data pipelines that supply ML models.
• Apply CI/CD practices, including automated testing and monitoring, to deploy ML models and application code successfully.
• Manage code to reduce vulnerabilities, govern models for risk, and follow Responsible and Explainable AI practices.
• Program using languages such as Python, Scala, or Java.

Technologies:

• AI
• AWS
• Azure
• Big Data
• CI/CD
• Cloud
• GCP
• Golang
• Support
• Java
• Kubernetes
• Machine Learning
• PyTorch
• Python
• Scala
• Spark
• TensorFlow
• numpy
• pandas
• Model Training

More

We are seeking a Machine Learning Engineer 4 for our Machine Learning Foundations (MLX) team at Capital One. Our collaborative, inclusive, iterative environment brings together makers and problem-solvers to address customer and business needs. In this role, you can help advance AI initiatives and scale production models using open-source frameworks, algorithms, and emerging technologies. The role includes performance-based incentives and a comprehensive benefits package supporting health, financial, and overall well-being; eligibility varies by employment status and level. Listed annual salary ranges are $179,400–$204,700 for the sales territory and Richmond, VA; $197,300–$225,100 in McLean, VA; and $215,200–$245,600 in New York, NY and San Jose, CA. Pay varies by work location, and part-time salaries are prorated. Applications are expected to remain open for at least five business days. We are an equal opportunity employer and provide consideration in accordance with applicable laws.

last updated 43 week of 2026