Capital One is seeking a Senior Lead Machine Learning Engineer in McLean, VA (onsite) to productionize machine learning applications and systems at scale. The role will design, build, deploy, and monitor reinforcement learning-based recommender systems that enable personalized digital experiences across Mobile, Web, and Email.
Responsibilities
- Design, build, and/or deliver machine learning models and components that address real-world business needs in collaboration with Product and Data Science teams.
- Guide machine learning infrastructure decisions through hands-on understanding of modeling techniques and tradeoffs, including model selection, data and feature selection, model training, hyperparameter tuning, dimensionality, bias/variance, and validation.
- Solve complex problems by writing and testing application code, developing and validating machine learning models, and automating tests and deployment.
- Work within a cross-functional Agile team to create and enhance software that supports large-scale big data and ML applications.
- Retrain, maintain, and monitor models operating in production.
- Use, build, and apply cloud-based architectures, technologies, and platforms to deliver optimized ML models at scale.
- Construct optimized data pipelines to provide inputs for machine learning models.
- Apply continuous integration and continuous deployment best practices, including test automation and monitoring, to support reliable deployments.
- Ensure code is well-managed to reduce vulnerabilities, that models are governed from a risk perspective, and that machine learning follows Responsible and Explainable AI best practices.
- Use programming languages including Python, Scala, or Java.
Requirements
- Bachelor’s Degree.
- 8+ years of experience designing and building data-intensive solutions using distributed computing (internship experience does not apply).
- 4+ years of programming experience with Python, Scala, or Java.
- 3+ years building, scaling, and optimizing ML systems.
- 2+ years leading teams developing ML solutions.
Technologies
- Python, Scala, Java
- AWS, Azure, Google Cloud Platform
- scikit-learn, PyTorch
- Dask, Spark
- TensorFlow
About the Team
Within Card Tech, the Customer Intelligent Decisions & Experiences (CIDX) team is building the next generation of large-scale, reinforcement learning-based recommender systems. These systems power personalized experiences across marketing, customer servicing, and digital products for millions of Card and MainStreet customers.
The team also contributes reusable capabilities to a Capital One-wide Experimentation Platform, enabling users across the enterprise to apply machine learning for a variety of use cases.
Preferred Qualifications
- Master’s or Doctoral Degree in computer science, electrical engineering, mathematics, or a similar field.
- Experience developing and deploying ML solutions in a public cloud such as AWS, Azure, or Google Cloud Platform.
- 4+ years of on-the-job experience with an industry-recognized ML framework such as scikit-learn, PyTorch, Dask, Spark, or TensorFlow.
- 3+ years of experience developing performant, resilient, and maintainable code.
- 3+ years of experience with data gathering and preparation for ML models.
- 3+ years of people management experience.
- ML industry impact through conference presentations, papers, blog posts, open source contributions, or patents.
- 3+ years of experience building production-ready data pipelines that feed ML models.
- Ability to communicate complex technical concepts clearly to a variety of audiences.
- Experience leveraging interactive AI tooling to accelerate productivity, using capabilities beyond basic code completion.
Compensation and Benefits
Salary Range: USD 229,900 - 262,400 per yearly.
- 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 to support total well-being.
