Machine Learning Engineer 4

Capital One is hiring a Machine Learning Engineer to design, build, deliver, and productionize machine learning models and 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 while supporting responsible, explainable, and well-governed AI practices.

What you’ll do

• Design, build, and/or deliver ML models and components that address real business problems in collaboration with Product and Data Science teams
• Shape ML infrastructure decisions using knowledge of modeling techniques and common issues, including model choice, data and feature selection, training, hyperparameter tuning, dimensionality, bias/variance, and validation
• Solve complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployments
• Work within a cross-functional Agile team to create and improve software that supports advanced big data and ML applications
• Retrain, maintain, and monitor models in production
• Leverage or build cloud-based architectures, technologies, and/or platforms to deliver optimized ML models at scale
• Construct optimized data pipelines that feed ML models
• Apply continuous integration and continuous deployment practices, including test automation and monitoring, to support successful production releases
• Manage code to reduce vulnerabilities, ensure models are governed from a risk perspective, and follow best practices in Responsible and Explainable AI
• Use 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 using industry frameworks PyTorch or TensorFlow and libraries such as Pandas, NumPy, Scikit-learn
• At least 4 years of experience working with and operating large-scale distributed systems (such as Spark and Ray) to prepare AI/ML data
• At least 2 years deploying and operating Machine Learning solutions in production, including production services in the cloud (AWS, GCP, Azure) and using Kubernetes to manage large-scale containerized ML systems

Technologies

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

Compensation and location

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

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) across model types (Regression, Classification, Clustering), model architectures (RNNs, CNNs, LSTMs, Transformers), and training concepts (loss function, hyperparameters, regularization) including evaluating model accuracy and diagnosing 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 an ML technique, model, or proof of concept

Additional information

• Capital One will not sponsor a new applicant for employment authorization or provide immigration-related support for this position
• This role is expected to accept applications for a minimum of 5 business days
• No agencies please
• Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable laws
• Capital One promotes a drug-free workplace
• If you visited the website and need an accommodation, contact Capital One Recruiting at 1-800-304-9102 or [email protected]
• For technical support or recruiting process questions, email [email protected]
• Capital One does not guarantee third-party products, services, educational tools, or other information available through the site
• Capital One Financial is made up of several different entities (Canada/UK/Philippines posting entity notes)