Machine Learning Engineer 4

Capital One is seeking a Machine Learning Engineer 4 to design, build, deliver, and productionize machine learning models and the supporting components. In this onsite role in McLean, VA, you will work closely with Product and Data Science teams to deploy ML solutions at scale and keep models monitored, governed, and aligned with Responsible and Explainable AI practices.

What you’ll do

• Design, build, and/or deliver ML models and components that address real-world business needs in collaboration with Product and Data Science teams
• Guide ML infrastructure decisions using knowledge of modeling techniques and issues, including model selection, data and feature selection, training, hyperparameter tuning, dimensionality, bias/variance, and validation
• Solve complex problems through application code development and testing, ML model development and validation, and automation of tests and deployment
• Collaborate in a cross-functional Agile team to create and improve software enabling state-of-the-art big data and ML applications
• Retrain, maintain, and monitor ML models in production
• Use or build cloud-based architectures, technologies, and/or platforms to deliver optimized ML models at scale
• Construct optimized data pipelines to supply ML models
• Apply continuous integration and continuous deployment practices, including test automation and monitoring, to support successful deployments of models and application code
• Maintain well-managed code to reduce vulnerabilities, ensure models are governed from a risk perspective, and follow Responsible and Explainable AI best practices
• Work with programming languages such as Python, Scala, or Java

Requirements

• 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 with industry frameworks including PyTorch or Tensorflow, and libraries such as Pandas, NumPy, Scikit-learn
• At least 4 years operating large scale distributed systems such as Spark and Ray for AI/ML data preparation
• At least 2 years deploying and operating ML solutions in production and operating production services in the cloud (AWS, GCP, Azure), including using Kubernetes to manage large scale containerized ML software systems

Technologies

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

Benefits

• Comprehensive, competitive, and inclusive set of health, financial and other benefits

Preferred qualifications

• Master’s or doctoral degree in computer science, electrical engineering, mathematics, or 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 ML techniques (Supervised, semi-supervised, and unsupervised, reinforcement learning) and model types (Regression, Classification, Clustering), plus architectures (RNNs, CNNs, LSTMs, Transformers)
• 3+ years of experience evaluating model accuracy and diagnosing and addressing issues such as underfitting and overfitting
• 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/co-authored a paper on a ML technique, model, or proof of concept

Compensation and incentives

McLean, VA: $197,300 - $225,100 per year for Machine Learning Engineer 4. The role may also be eligible for performance-based incentive compensation, which may include cash bonus(es) and/or long-term incentives (LTI).

Additional information

• Capital One will not sponsor a new applicant for employment authorization or provide immigration-related support for this position (including H1B, F-1 OPT, F-1 STEM OPT, F-1 CPT, J-1, TN, E-3, O-1, and other work authorization requiring employer immigration support)
• Expected to accept applications for a minimum of 5 business days
• No agencies please
• Equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws
• Capital One promotes a drug-free workplace
• If you need an accommodation, contact Capital One Recruiting at 1-800-304-9102 or [email protected]
• For technical support or questions about Capital One’s recruiting process, email [email protected]
• Capital One does not provide, endorse, or guarantee and is not liable for third-party products, services, educational tools, or other information available through this site
• Capital One Financial includes multiple different entities (Canada/UK/Philippines posting entity notes)