Machine Learning Engineer (Manager, IC)

Salary: $179,400 - 245,600 per year Requirements:

• Bachelors degree or higher in Computer Science, Machine Learning, or a related quantitative discipline 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 using standard frameworks such as PyTorch or TensorFlow and libraries like Pandas, NumPy, and Scikit-learn
• At least 4 years of experience working with 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 and running cloud-based production services on AWS, GCP, or Azure, including Kubernetes for large-scale containerized ML systems
• A masters or doctoral degree in Computer Science, Electrical Engineering, Mathematics, or a related field is preferred
• 3+ years of experience optimizing machine learning algorithms, configurations, and infrastructure is preferred
• 3+ years of experience applying software development best practices, including source control, testing, code reviews, and CI/CD, is preferred
• 3+ years of experience building resilient software solutions with pre-production testing, advanced deployment methods, monitoring, alerts, and incident response planning is preferred
• 3+ years of experience with machine learning techniques, model types, architectures, training concepts, and model evaluation is preferred
• 3+ years of experience designing, implementing, and scaling production-ready data pipelines for training and evaluating ML models is preferred
• 1+ years of experience as a technical lead developing ML solutions using industry best practices, patterns, and automation is preferred
• Experience authoring or co-authoring a paper on an ML technique, model, or proof of concept is preferred

• Design, build, and deliver ML models and components that address real business challenges in partnership with Product and Data Science teams
• Apply knowledge of ML modeling techniques and considerations to guide infrastructure decisions, including model choice, data and feature selection, training, tuning, dimensionality, bias/variance, and validation
• Solve complex problems by writing and testing application code, developing and validating ML models, and automating testing and deployment
• Work on a cross-functional Agile team to develop and enhance software for advanced big data and machine learning applications
• Retrain, maintain, and monitor models in production
• Use cloud-based architectures, technologies, and platforms to deliver optimized ML models at scale
• Build efficient data pipelines to supply ML models
• Apply continuous integration and continuous deployment practices, including test automation and monitoring, to support successful deployment of ML models and application code
• Ensure code is well managed to reduce vulnerabilities, models are governed from a risk perspective, and ML practices align with Responsible and Explainable AI
• Use programming languages such as Python, Scala, or Java

• 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 Capital One, a fast-paced, collaborative, inclusive, and iterative environment where makers, breakers, doers, and disruptors work together to solve real customer needs. We are seeking Machine Learning Engineers to help drive major AI transformations and scale production models across the company. This Machine Learning Engineer 4 role is based on the salary ranges listed for Chicago, IL and New York, NY, with other locations subject to the applicable pay range. The role may also be eligible for performance-based incentive compensation and a comprehensive, competitive, and inclusive benefits package that supports overall well-being. We are an equal opportunity employer committed to non-discrimination and a drug-free workplace.

last updated 40 week of 2026