Machine Learning Engineer 4 - Machine Learning Foundations (MLX)
Capital One2 days ago
Richmond, VA, USA +4 moreStaff+
Base Salary
$215k - $246k/yr
Responsibilities
- Design, build, and deliver machine learning models and components for real-world business problems.
- Make ML infrastructure decisions involving model selection, data and feature selection, training, hyperparameter tuning, dimensionality, bias and variance, and validation.
- Write and test application code, develop and validate ML models, and automate testing and deployment.
- Create and enhance software supporting large-scale data and machine learning applications.
- Retrain, maintain, and monitor production models.
- Build or leverage cloud-based architectures and platforms to deliver optimized ML models at scale.
- Construct optimized data pipelines that feed machine learning models.
- Apply continuous integration, continuous deployment, test automation, and monitoring practices.
- Manage code and model governance while supporting vulnerability reduction, Responsible AI, and Explainable AI practices.
Requirements
- Bachelor's degree or higher in Computer Science, Machine Learning, or a related quantitative field such as Statistics, Economics, Operations Research, Analytics, Mathematics, or Engineering.
- At least 4 years of programming experience with Python, Java, Golang, or C++.
- At least 4 years of machine learning experience using PyTorch or TensorFlow and Pandas, NumPy, and scikit-learn.
- At least 4 years of experience using and operating large-scale distributed systems such as Spark and Ray for AI or machine learning data.
- At least 2 years of experience deploying and operating machine learning solutions in production, operating production cloud services, and using Kubernetes for large-scale containerized ML systems.
- Preferred: Master's or doctoral degree in Computer Science, Electrical Engineering, Mathematics, or a related field.
- Preferred: 3+ years optimizing ML algorithms, configurations, and infrastructure; following software development practices; building resilient production software; applying ML techniques and architectures; and designing and scaling production-ready ML data pipelines.
- Preferred: 1+ year as a technical lead developing ML solutions using industry practices, patterns, and automation.
- Preferred: authorship or co-authorship of a paper on an ML technique, model, or proof of concept.
Benefits
- Comprehensive health, financial, and other benefits supporting total well-being, with eligibility varying by employment status and management level.
- Eligible for performance-based incentive compensation, including cash bonuses and/or long-term incentives.
- Annual salary varies by work location; the role is expected to accept applications for at least 5 business days.
Tech Stack
Apache SparkAWSAzureC++GoGoogle Cloud PlatformJavaKubernetesNumPyPandasPythonPyTorchscikit-learnTensorFlow
Categories
Data EngineeringML Engineering
About Capital One
Capital One is a U.S. consumer and commercial bank that offers credit cards, checking and savings accounts, auto financing, and lending to small and large businesses. It earns revenue from interest income and interchange/fees across its card and banking products, and develops cloud-based digital services. Founded in 1994, Capital One is publicly traded on the NYSE (COF) and is headquartered in McLean, Virginia.