Machine Learning Engineer 4

Capital One is driving major AI transformations, and this Machine Learning Engineer role supports the end-to-end lifecycle of production ML. You will design, build, deploy, monitor, and govern ML models and the data and software pipelines that power them, using modern cloud and distributed systems.

Location: Plano, TX (onsite)

Compensation: USD 179,400 - 204,700 per year

What you’ll do

• Carry out ML engineering activities that may include designing, building, and delivering ML models and components for real-world business problems in collaboration with Product and Data Science teams.
• Apply ML expertise to ML infrastructure decisions, including model selection, data and feature selection, training, hyperparameter tuning, dimensionality considerations, bias/variance tradeoffs, and validation.
• Solve complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment.
• Work within a cross-functional Agile team to create and enhance software for big data and ML applications.
• Retrain, maintain, and monitor models once they are in production.
• Leverage or build cloud-based architectures and platforms to deliver optimized ML models at scale.
• Construct optimized data pipelines to support ML model training and evaluation.
• Use CI/CD practices, including test automation and monitoring, to support successful releases of ML model and application code.
• Maintain well-managed code to reduce vulnerabilities, ensure risk-aware governance for models, and follow 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 4 years of programming experience with Python, Java, Golang, or C++.
• At least 4 years of Machine Learning experience using industry frameworks PyTorch or Tensorflow and libraries including Pandas, NumPy, Scikit-learn.
• At least 4 years operating large-scale distributed systems (such as Spark and Ray) to prepare AI or Machine Learning data.
• At least 2 years deploying and operating ML solutions in production and operating production services in the cloud (AWS, GCP, Azure), using Kubernetes for large-scale containerized ML systems.

Technologies you may work with

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

Benefits

• Performance-based incentive compensation eligibility, which may include cash bonus(es) and/or long term incentives (LTI).
• Comprehensive, competitive, and inclusive health, financial, and other benefits supporting total well-being (eligibility varies by full-time/part-time status, exempt/non-exempt status, and management level).

Preferred qualifications

• Master’s or Doctoral Degree in Computer Science, Electrical Engineering, Mathematics, or a related field.
• 3+ years optimizing ML algorithms, configurations, and infrastructure.
• 3+ years following software development best practices including source control, testing, code reviews, and CI/CD.
• 3+ years building resilient software with pre-production testing, advanced deployment techniques (one-box, blue/green, gradual dial-up), monitoring and alarms, and preparing incident response plans.
• 3+ years applying Machine Learning techniques such as supervised, semi-supervised, unsupervised, and reinforcement learning, across model types (Regression, Classification, Clustering), architectures (RNNs, CNNs, LSTMs, Transformers), training concepts (loss function, hyperparameters, regularization), and model evaluation and debugging (underfitting, overfitting).
• 3+ years designing, implementing, and scaling production-ready data pipelines for training and evaluating ML models.
• 1+ years of technical lead experience developing ML solutions using best practices, patterns, and automation.
• Authored or co-authored a paper on an ML technique, model, or proof of concept.

Additional notes: This position is not eligible for employer-sponsored new applicants for employment authorization or immigration-related support (including H1B, F-1 OPT, F-1 STEM OPT, F-1 CPT, J-1, TN, E-3, O-1, and other forms of work authorization requiring employer immigration support). Applications are expected to be accepted for a minimum of 5 business days. No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) and 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 the recruiting process, email [email protected].