Machine Learning Engineer 5

Capital One is hiring a Machine Learning Engineer 5 (onsite) in Richmond, VA to design, build, scale, deploy, and monitor ML models and platforms that address business needs.

Responsibilities

• Design, build, and/or deliver ML models and components in collaboration with Product and Data Science teams
• Build and scale massive multi-tenant platforms for large-footprint ML training and/or serving
• Apply ML modeling expertise to guide infrastructure and modeling decisions, including model selection, 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 deployment
• Collaborate in a cross-functional Agile team to create and enhance software for big data and ML applications
• Retrain, maintain, and monitor models in production
• Use 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 CI/CD best practices, including test automation and monitoring, to support successful deployment of ML models and application code
• Ensure code is well-managed to reduce vulnerabilities, models are well-governed from a risk perspective, and ML follows Responsible and Explainable AI best practices
• 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 6 years of experience programming with Python, Java, Golang, or C++
• At least 6 years of Machine Learning experience using industry-standard frameworks PyTorch or Tensorflow and libraries (Pandas, NumPy, Scikit-learn)
• At least 6 years operating large-scale distributed systems (Spark, Ray) to prepare AI/ML data
• At least 4 years deploying and operating Machine Learning solutions in production, including operating production services in the cloud (AWS, GCP, Azure) and using Kubernetes for large-scale containerized ML systems

Technologies

• Python, Scala, Java, Golang, C++
• PyTorch, Tensorflow
• Pandas, NumPy, Scikit-learn
• Spark, Ray
• AWS, GCP, Azure
• Kubernetes
• CI/CD, continuous integration, continuous deployment

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 supporting total well-being

Preferred Qualifications

• Master’s or doctoral degree in computer science, electrical engineering, mathematics, or related field
• 5+ years of experience optimizing ML algorithms, configurations, and infrastructure
• 5+ years following software development best practices including source control, testing, code reviews, CI/CD, etc.
• 5+ years building resilient software solutions with pre-production testing, advanced deployment techniques (one-box, blue/green, gradual dial-up), monitoring, alarms, and incident response plan preparation
• 5+ years working with ML techniques (Supervised, semi-supervised, and unsupervised, reinforcement learning, etc.), model types (Regression, Classification, Clustering, etc.), model architectures (RNNs, CNNs, LSTMs, Transformers), training concepts (loss function, hyperparameters, regularization), and evaluating model accuracy plus diagnosing and addressing underfitting and overfitting
• 5+ years designing, implementing, and scaling production-ready data pipelines for training and evaluating ML models
• ML industry impact through conference presentations, papers, blog posts, open source contributions, or patents
• Ability to communicate complex technical and machine learning concepts clearly to a variety of audiences

Location

• Richmond, VA (onsite)

Compensation

• USD 209,000 - 238,500 per year

Other

• Capital One will consider sponsoring a new qualified applicant for employment authorization for this position
• Applications may close after 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 federal, state, and local laws
• Capital One promotes a drug-free workplace
• Capital One will consider for employment qualified applicants with a criminal history consistent with applicable laws regarding criminal background inquiries
• Accommodation for applicants available via Capital One Recruiting at 1-800-304-9102 or [email protected]
• Technical support/questions about recruiting process: [email protected]
• Capital One does not provide, endorse, or guarantee third-party products, services, educational tools, or other information available through this site
• Capital One Financial is made up of several different entities; postings may vary by country (Canada, United Kingdom, Philippines)