Machine Learning Engineer (IC)

Salary: $197,300 - 245,600 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 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 using and operating large-scale distributed systems, such as Spark or Ray, to prepare AI/ML 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 ML 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 applying software development practices such as source control, testing, code reviews, and CI/CD. Preferred: 3+ years of experience building resilient software with pre-production testing, advanced deployment methods, monitoring, alarms, and incident response planning. Preferred: 3+ years of experience with ML techniques, model types and architectures, training concepts, and methods for evaluating 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 practices, patterns, and automation. Preferred: Authored or co-authored a paper on an ML technique, model, or proof of concept. Responsibilities: Design, build, and deliver ML models and components to address business problems in partnership with Product and Data Science teams. Apply knowledge of modeling methods and challenges—including model, data, and feature selection, training, hyperparameter tuning, dimensionality, bias and variance, and validation—to guide ML infrastructure decisions. Solve complex problems by writing and testing application code, developing and validating models, and automating tests and deployments. Work with a cross-functional Agile team to develop and improve software for 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 support successful deployment of models and application code. Manage code to reduce vulnerabilities, govern models for risk, and apply Responsible and Explainable AI practices. Use programming 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 hiring a Machine Learning Engineer 4 to help advance AI and scale production models at Capital One. Our collaborative, inclusive, iterative environment brings together makers and problem-solvers focused on customer needs, and the role works across disciplines including Operations, Modeling, and Data Engineering. The position is available in Cambridge, MA and McLean, VA, with listed annual salary ranges of $197,300–$225,100, and in New York, NY, San Francisco, CA, and San Jose, CA, with ranges of $215,200–$245,600; pay for other locations varies. The role is also eligible for performance-based incentives and our health, financial, and other benefits, with eligibility depending on role status and level. We do not sponsor new employment authorization applicants or provide immigration-related support for this position. We are an equal opportunity employer and maintain a drug-free workplace. last updated 39 week of 2026