Senior Machine Learning Engineer

Salary: $209,000 - 286,200 per year Requirements:

• We require a bachelors degree.
• We need at least 8 years of experience designing and building data-intensive solutions using distributed computing; internship experience does not count.
• We require at least 4 years of programming experience with Python, Scala, or Java.
• We need at least 3 years of experience building, scaling, and optimizing machine learning systems.
• We require at least 2 years of experience leading teams that develop machine learning solutions.
• Preferred: a masters or doctoral degree in computer science, electrical engineering, mathematics, or a related discipline.
• Preferred: experience developing and deploying machine learning solutions in a public cloud such as AWS, Azure, or Google Cloud Platform.
• Preferred: 4+ years of hands-on experience with an industry-recognized ML framework such as scikit-learn, PyTorch, Dask, Spark, or XGBoost.
• Preferred: 3+ years of experience developing performant, resilient, and maintainable code.
• Preferred: 3+ years of experience gathering and preparing data for machine learning models.
• Preferred: 3+ years of people management experience.
• Preferred: demonstrated ML industry impact through conference presentations, papers, blog posts, open-source contributions, or patents.
• Preferred: 3+ years of experience building production-ready data pipelines that feed machine learning models.
• Preferred: ability to communicate complex technical ideas clearly to varied audiences.
• Preferred: experience using interactive AI tools to boost productivity beyond basic code completion.

• We design, build, and deliver machine learning models and components that address real business problems in partnership with Product and Data Science.
• We guide infrastructure decisions using our understanding of ML modeling approaches, including model choice, data and feature selection, training, hyperparameter tuning, dimensionality, bias/variance, and validation.
• We solve complex problems by writing and testing application code, developing and validating ML models, and automating testing and deployment.
• We collaborate on cross-functional Agile teams to build and enhance software for advanced big data and machine learning applications.
• We retrain, maintain, and monitor models in production.
• We leverage or create cloud-based architectures, technologies, and platforms to deliver optimized ML models at scale.
• We build efficient data pipelines that support ML models.
• We apply continuous integration and continuous deployment practices, including test automation and monitoring, to support reliable deployment of ML models and application code.
• We ensure code is carefully managed to reduce vulnerabilities, models are well governed from a risk standpoint, and our ML practices align with Responsible and Explainable AI principles.
• We use programming languages such as Python, Scala, or Java.

• AI
• AWS
• Azure
• Big Data
• Cloud
• Support
• Java
• Machine Learning
• PyTorch
• Python
• Scala
• Spark
• Model Training

More:

We are Capital One, and this role sits within an Agile machine learning team focused on productionizing ML applications and systems at scale. We offer comprehensive, competitive, and inclusive health, financial, and other benefits that support total well-being, along with eligibility for performance-based incentives that may include cash bonuses and/or long-term incentives. Salary ranges vary by location, including McLean, Richmond, and New York, and we consider candidates for other locations based on the applicable local pay range. We are an equal opportunity employer committed to a drug-free workplace and to non-discrimination, and we may sponsor qualified applicants for employment authorization. This position is open to applications for a minimum of 5 business days.

last updated 35 week of 2026