Machine Learning Engineer 4 (Manager, IC)

Capital One is seeking a Machine Learning Engineer 4 (Manager, IC) in Chicago, IL (onsite) to design, build, deploy, and monitor production machine learning models and supporting components at scale. The role partners with Product and Data Science teams and applies cloud and CI/CD practices to deliver reliable ML systems.

What You’ll Do

• Design, build, and deliver ML models and components to solve real-world business problems in collaboration with Product and Data Science teams
• Use expertise in ML modeling techniques and practical challenges to guide infrastructure decisions, including model and data selection, feature selection, training, hyperparameter tuning, dimensionality, bias/variance considerations, and validation
• Address complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment
• Work within a cross-functional Agile team to create and improve software supporting big data and ML applications
• Retrain, maintain, and monitor production models
• Leverage and/or build cloud-based architectures, technologies, and platforms to deliver optimized ML models at scale
• Construct optimized data pipelines to supply ML models
• Apply continuous integration and continuous deployment best practices, including test automation and monitoring, to support successful model and application releases
• Maintain well-managed code to reduce vulnerabilities, ensure ML governance from a risk perspective, and follow best practices in Responsible and Explainable AI
• Use programming languages such as Python, Scala, or Java

Required Qualifications

• Bachelor’s Degree or higher in Computer Science, Machine Learning, or a related quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Engineering)
• At least 4 years of experience programming with Python, Java, Golang, or C++
• At least 4 years of Machine Learning experience using industry standard frameworks PyTorch or Tensorflow and libraries such as Pandas, NumPy, Scikit-learn
• At least 4 years of experience using and operating large-scale distributed systems (Spark, Ray) to prepare AI or Machine Learning data
• At least 2 years of experience deploying and operating Machine Learning solutions in production, operating production services in cloud environments (AWS, GCP, Azure), and using Kubernetes to manage large-scale containerized ML systems

Preferred Qualifications

• Master’s or Doctoral Degree in Computer Science, Electrical Engineering, Mathematics, or a related field
• 3+ years of experience optimizing ML algorithms, configurations, and infrastructure
• 3+ years of experience following software development best practices, including source control, testing, code reviews, and CI/CD
• 3+ years of experience building resilient software solutions with pre-production testing, advanced deployment techniques (one-box, blue/green, gradual dial-up), monitoring, alarms, and preparing incident response plans
• 3+ years of experience with Machine Learning techniques and model types, including supervised, semi-supervised, unsupervised, and reinforcement learning; regression, classification, and clustering; as well as architectures such as RNNs, CNNs, LSTMs, and Transformers
• 3+ years of experience with training concepts (loss function, hyperparameters, regularization) and evaluating model accuracy, diagnosing issues (underfitting, overfitting), and addressing them
• 3+ years of experience designing, implementing, and scaling production-ready data pipelines for training and evaluating ML models
• 1+ years of experience as a technical lead developing ML solutions using industry best practices, patterns, and automation
• Authored or co-authored a paper on a ML technique, model, or proof of concept

Technologies

• Python, Scala, Java, Golang, C++
• PyTorch, Tensorflow
• Pandas, NumPy, Scikit-learn
• Spark, Ray
• AWS, GCP, Azure
• Kubernetes

Benefits

• Performance-based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI)
• Comprehensive, competitive, and inclusive set of health, financial, and other benefits

Compensation

• Chicago, IL: USD 179,400 - 204,700 per year
• New York, NY: USD 215,200 - 245,600 per year