Machine Learning Engineer 4 - Machine Learning Foundations (MLX)

Capital One • San Jose, CA

2d • $215,200 - $245,600

About The Position

Capital One is seeking a Machine Learning Engineer to help drive AI transformation and scale production models. The role spans machine learning engineering, operations, modeling, and data engineering, and involves collaborating with Product and Data Science teams and contributing to a cross-functional Agile team. The engineer will develop and maintain ML models and components, build cloud-based ML infrastructure and data pipelines, and apply continuous integration, deployment, monitoring, security, governance, and Responsible and Explainable AI practices. Programming languages may include Python, Scala, or Java.

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 industry-standard frameworks such as PyTorch or TensorFlow and libraries such as Pandas, NumPy, and Scikit-learn.
• At least 4 years of experience using and operating large-scale distributed systems such as Spark or 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 the cloud (AWS, GCP, or Azure), and using Kubernetes to manage large-scale containerized ML software systems.

Nice To Haves

• 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 with software development best practices, including source control, testing, code reviews, and CI/CD.
• 3+ years of experience building resilient software solutions using pre-production testing, advanced deployment techniques (one-box, blue/green, gradual dial-up), monitoring, alarms, and incident response plans.
• 3+ years of experience with machine learning techniques, model types, architectures, training concepts, model evaluation, 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 or co-authored a paper on an ML technique, model, or proof of concept.

Responsibilities

• Design, build, and deliver ML models and components that address business problems in collaboration with Product and Data Science teams.
• Inform ML infrastructure decisions based on knowledge of modeling techniques and issues, including model and data selection, 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 to solve complex problems.
• Collaborate with a cross-functional Agile team to create and enhance software for big data and machine learning applications.
• Retrain, maintain, and monitor models in production.
• Leverage or build cloud-based architectures, technologies, and platforms to deliver optimized ML models at scale.
• Construct optimized data pipelines to feed ML models.
• Apply CI/CD best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code.
• Manage code to reduce vulnerabilities, govern models from a risk perspective, and follow Responsible and Explainable AI best practices.
• Use programming languages such as Python, Scala, or Java.

Benefits

• Comprehensive health, financial, and other benefits supporting total well-being.
• Performance-based incentive compensation, which may include cash bonuses and/or long-term incentives.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior