Machine Learning Engineer 5 (Senior Manager, IC)

Capital One is seeking a Machine Learning Engineer to design, build, and scale machine learning models and platforms. The role covers end-to-end ML engineering, including production deployment, monitoring, and operational practices at scale, with collaboration across product and data science.

Key Responsibilities

• Design, build, and deliver ML models and components to address real-world business problems in partnership with Product and Data Science teams.
• Build and scale multi-tenant platforms to support large-footprint ML model training and/or serving.
• Apply ML modeling expertise to guide infrastructure decisions, including model and data/feature selection, training approaches, hyperparameter tuning, dimensionality, and bias/variance tradeoffs, along with validation.
• Solve complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment.
• Collaborate within a cross-functional Agile team to create and improve software for big data and ML applications.
• Retrain, maintain, and monitor models in production environments.
• Use or build cloud-based architectures, technologies, and 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 releases of ML models and application code.
• Ensure code is well-managed to reduce vulnerabilities, support risk-governed model practices, and follow Responsible and Explainable AI best practices.
• Use programming languages such as Python, Scala, or Java.

Required Qualifications

• 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 with industry-standard frameworks PyTorch or Tensorflow, and libraries including Pandas, NumPy, and Scikit-learn.
• At least 6 years of experience using and operating large-scale distributed systems (Spark, Ray) to prepare AI or Machine Learning data.
• At least 4 years of experience deploying and operating ML solutions in production, including operating production services in AWS, GCP, or Azure, and using Kubernetes for large-scale containerized ML systems.
• Master's or Doctoral Degree in Computer Science, Electrical Engineering, Mathematics, or a related field.
• 5+ years of experience optimizing ML algorithms, configurations, and infrastructure.
• 5+ years of experience following software development best practices, including source control, testing, code reviews, and CI/CD.
• 5+ years of experience building resilient software solutions with pre-production testing, advanced deployment techniques (one-box, blue/green, gradual dial-up), monitoring and alarms, and incident response planning.
• 5+ years of experience working with supervised, semi-supervised, and unsupervised techniques, including reinforcement learning; model types such as Regression, Classification, and Clustering; architectures such as RNNs, CNNs, LSTMs, and Transformers; and concepts including loss functions, hyperparameters, and regularization, including evaluating model accuracy and diagnosing underfitting and overfitting.
• 5+ years of experience designing, implementing, and scaling production-ready data pipelines for training and evaluating ML models.
• Demonstrated ML industry impact through conference presentations, papers, blog posts, open source contributions, or patents.
• Ability to clearly communicate complex technical and ML concepts to a variety of audiences.

Technologies

Python, Scala, Java, Golang, C++, PyTorch, Tensorflow, Pandas, NumPy, Scikit-learn, Spark, Ray, AWS, GCP, Azure, Kubernetes, CI/CD, and ML architectures including RNNs, CNNs, LSTMs, Transformers.

Compensation

Salary range for this role in New York, NY is USD 250,800 - 286,200 per year.

Additional location ranges listed by the employer: Cambridge, MA ($229,900 - $262,400), McLean, VA ($229,900 - $262,400), San Francisco, CA ($250,800 - $286,200), San Jose, CA ($250,800 - $286,200).

Benefits

• Eligible for 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.

Location and Contact

Location: New York, NY (onsite).

• If you require application or employment accommodation: 1-800-304-9102 and [email protected].
• For technical support or questions about the recruiting process: [email protected].

Education

Bachelor's Degree or higher (Master's or Doctoral Degree also listed as a requirement).