Senior Machine Learning Engineer (AI Foundations)

The Senior Machine Learning Engineer, AI Foundations, contributes to Capital One's production ML initiatives within an Agile team. The role centers on scalable ML architecture, code review for models and applications, and ensuring the reliability and performance of ML systems, with opportunities to apply contemporary ML engineering practices.

Compensation

Salary: USD 161,800 - 184,600 per year.

Responsibilities

• Design, build, and deliver ML models and components that address real business needs, collaborating with Product and Data Science teams.
• Guide ML infrastructure decisions based on modeling techniques and issues, including model choice, data and feature selection, training, hyperparameter tuning, dimensionality, bias/variance, and validation.
• Address complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment.
• Collaborate within a cross-functional Agile team to create and enhance software enabling state-of-the-art big data and ML applications.
• Retrain, maintain, and monitor models in production.
• Leverage or build cloud-based architectures, technologies, and platforms to deliver optimized ML models at scale.
• Construct optimized data pipelines to feed ML models.
• Apply continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code.
• Ensure all code is well-managed to reduce vulnerabilities, models are well-governed from a risk perspective, and the ML practices align with Responsible and Explainable AI.
• Use programming languages such as Python, Scala, or Java.

Requirements

• Bachelor’s Degree.
• At least 4 years of experience programming with Python, Scala, or Java (Internship experience does not apply).
• At least 3 years of experience designing and building data-intensive solutions using distributed computing.
• At least 2 years of on-the-job experience with industry-recognized ML frameworks (scikit-learn, PyTorch, Dask, Spark, or TensorFlow).
• At least 1 year of experience productionizing, monitoring, and maintaining models.

Technologies

• Python
• Scala
• Java
• scikit-learn
• PyTorch
• Dask
• Spark
• TensorFlow

Benefits

• Health benefits
• Financial benefits
• Performance-based incentive compensation (cash bonuses and/or long-term incentives)