Senior Manager, Machine Learning Engineer - Plano

Salary: $209,000 - 286,200 per year 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 6 years of programming experience with Python, Java, Golang, or C++
• At least 6 years of machine learning experience with PyTorch or TensorFlow and libraries such as Pandas, NumPy, or Scikit-learn
• At least 6 years of experience using and operating large-scale distributed systems such as Spark or Ray to prepare AI or machine learning data
• At least 4 years of experience deploying and operating machine learning solutions in production, running cloud production services on AWS, GCP, or Azure, and using Kubernetes to manage large-scale containerized ML systems
• At least 1 year of people leadership experience
• Preferred: Masters or doctoral degree in Computer Science, Electrical Engineering, Mathematics, or a related field
• Preferred: 3 or more years managing and leading an ML engineering team
• Preferred: 5 or more years optimizing ML algorithms, configurations, and infrastructure
• Preferred: 5 or more years applying software development practices such as source control, testing, code reviews, and CI/CD
• Preferred: 5 or more years building resilient software solutions using pre-production testing, deployment approaches such as one-box, blue/green, or gradual dial-up, monitoring, alarms, and incident response plans
• Preferred: 5 or more years working with ML techniques, model types and architectures, training concepts, and model evaluation and troubleshooting
• Preferred: 5 or more years designing, implementing, and scaling production-ready data pipelines for training and evaluating ML models
• Preferred: Demonstrated ML industry impact through conference presentations, papers, blog posts, open-source contributions, or patents

• Design, build, and deliver machine learning models and components for business problems in partnership with Product and Data Science teams
• Build and scale multi-tenant platforms for large-scale model training and serving
• Apply knowledge of modeling methods and considerations—including model and feature selection, training, hyperparameter tuning, dimensionality, bias and variance, and validation—to infrastructure decisions
• Solve complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployments
• Work on cross-functional Agile teams to create and improve software for advanced big data and ML applications
• Retrain, maintain, and monitor production models
• Use or build cloud architectures and platforms to deliver optimized ML models at scale
• Build optimized data pipelines for ML models
• Apply CI/CD practices, test automation, and monitoring to support reliable model and application deployments
• Manage code and model risk, and apply Responsible and Explainable AI practices
• Contribute hands-on technical expertise and innovation while mentoring peers and junior engineers
• Recruit, develop, and retain engineering talent
• Stay current with technology trends, explore new tools, participate in technology communities, and mentor the engineering community

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

More:

We are hiring a Senior Manager, Machine Learning Engineer to help advance AI transformation and scale production models at Capital One. Our collaborative, inclusive, iterative environment brings together teams focused on solving real customer and business problems. The role offers a full-time annual salary range of $229,900–$262,400 in McLean, Virginia; $250,800–$286,200 in New York, New York; $209,000–$238,500 in Plano, Texas; and $250,800–$286,200 in San Francisco, California. Pay ranges vary by work location, and the offer letter will state the salary offered. The role is eligible for performance-based incentives, which may include cash bonuses or long-term incentives. We provide a comprehensive benefits package supporting health, financial, and overall well-being, with eligibility based on employment status and management level. We are an equal opportunity employer and maintain a drug-free workplace.

last updated 43 week of 2026