Senior Machine Learning Engineer, Bank Technology
3 weeks ago
As a Senior Machine Learning Engineer at Capital One, you will join an Agile team focused on deploying innovative machine learning applications and systems at scale. Your role will involve the detailed technical design, development, and implementation of cutting-edge machine learning applications using advanced technology platforms. This position emphasizes machine learning architecture, including the development and review of model and application code, while ensuring high availability and performance of our applications. You’ll have ample opportunity to learn continuously and implement the latest advancements in machine learning engineering.
Key Responsibilities:
Collaboratively design and deliver machine learning models and components that address real business challenges alongside Product and Data Science teams.
Utilize your understanding of ML modeling techniques to inform infrastructure decisions, including model selection, data features, training, and validation processes.
Address complex problems through writing and testing application code, developing ML models, and automating testing and deployment processes.
Work within a cross-functional Agile team to enhance software that enables advanced big data and machine learning applications.
Manage the retraining, maintenance, and monitoring of models in production to ensure optimal performance.
Leverage or construct cloud architectures and platforms to deploy optimized ML models at scale.
Build efficient data pipelines to support machine learning models.
Employ continuous integration and deployment best practices to guarantee smooth deployment of ML models and application code.
Ensure code management reduces vulnerabilities and that models comply with risk governance practices, adhering to Responsible and Explainable AI standards.
Engage in programming using languages such as Python, Scala, or Java.
Basic Qualifications:
Bachelor's degree.
Minimum of 6 years of experience in designing and building data-intensive solutions using distributed computing (Internship experience not applicable).
At least 4 years of programming experience with Python, Scala, or Java.
A minimum of 2 years of experience in building, scaling, and optimizing ML systems.
Preferred Qualifications:
Master's or PhD in computer science, electrical engineering, mathematics, or a related field.
3+ years of experience in constructing production-ready data pipelines for machine learning models.
3+ years of practical experience with industry-standard ML frameworks like scikit-learn, PyTorch, Dask, Spark, or TensorFlow.
2+ years of experience writing efficient, maintainable, and robust code.
2+ years of experience in data gathering and preparation for machine learning models.
2+ years in a leadership role managing teams.
1+ years of experience leading teams in developing ML solutions using best practices, patterns, and automation.
Experience deploying ML solutions in public cloud environments such as AWS, Azure, or Google Cloud Platform.
Expertise in designing, implementing, and optimizing complex data pipelines for ML models and assessing their performance.
Contributions to the ML industry through conference presentations, publications, blogs, open source contributions, or patents.
This position is based at Capital One, located at Center 1, 19052, McLean, Virginia. Capital One offers a competitive and inclusive range of health, financial, and other benefits to support your overall well-being. Please be aware that Capital One will not be sponsoring a new applicant for employment authorization for this role.
Capital One is an equal opportunity employer committed to diversity and inclusion in the workplace. All qualified applicants will receive consideration for employment without regard to sex, race, color, age, national origin, religion, disability, genetic information, marital status, sexual orientation, gender identity, gender reassignment, citizenship, immigration status, or protected veteran status.
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