Machine Learning Engineer

About The Company

Capital One is a leading diversified bank renowned for its innovative approach to financial services and technology-driven solutions. With a strong focus on customer-centric banking, Capital One leverages cutting-edge technology to deliver personalized financial products and services. The company prides itself on fostering a collaborative and inclusive workplace environment, emphasizing continuous learning, innovation, and integrity. As a pioneer in the financial industry, Capital One is committed to leveraging data, analytics, and technology to create value for its customers, employees, and shareholders. The organization operates across various segments, including credit cards, auto loans, and savings accounts, with a growing emphasis on digital transformation and enterprise platform development.

About The Role

The Lead Machine Learning Engineer at Capital One plays a pivotal role in transforming data-driven insights into scalable, production-ready machine learning solutions. This position is integral to the Enterprise Platforms Technology team, focusing on developing and operationalizing sophisticated ML models that enhance customer experiences and drive business growth. The role involves collaborating with cross-functional teams, including data scientists, software engineers, and product managers, to design, build, and deploy innovative ML applications. The engineer will be responsible for architecting robust ML systems, ensuring high performance, scalability, and compliance with responsible AI practices. This opportunity offers a dynamic environment where you can lead complex projects, influence technological advancements, and contribute to the company's digital transformation initiatives.

Qualifications

The ideal candidate will possess a strong educational background and extensive professional experience in data engineering, machine learning, and software development. A bachelor’s degree in computer science, electrical engineering, mathematics, or a related field is required, with a preference for candidates holding a master’s or doctoral degree. You should have at least six years of experience designing and implementing data-intensive solutions using distributed computing frameworks. Proficiency in programming languages such as Python, Scala, or Java is essential, along with a minimum of four years of hands-on experience in these languages. Additionally, candidates should have at least two years of experience building, scaling, and optimizing ML systems in production environments. Industry-recognized ML frameworks like scikit-learn, PyTorch, TensorFlow, or Spark are highly desirable. Leadership experience, cloud platform expertise (AWS preferred), and a proven track record of developing resilient, maintainable, and high-performance data pipelines will set candidates apart.

Responsibilities

• Design, develop, and deploy machine learning models and components that address complex business challenges, collaborating closely with product and data science teams.
• Make informed decisions on ML infrastructure, including model selection, feature engineering, hyperparameter tuning, and validation techniques to ensure optimal model performance.
• Develop, test, and automate application code to facilitate the deployment and monitoring of ML models in production environments.
• Participate as a key member of Agile teams, contributing to the creation and enhancement of scalable software solutions for big data and ML applications.
• Maintain and retrain models in production, ensuring their continued accuracy and relevance through ongoing monitoring and updates.
• Leverage cloud-based architectures and platforms, primarily AWS, to deploy and manage ML models at scale efficiently.
• Construct and optimize data pipelines that supply high-quality data for ML training and inference.
• Implement best practices in CI/CD, including automated testing and deployment, to ensure reliable and secure model delivery.
• Ensure all code adheres to security standards, governance policies, and responsible AI principles, emphasizing transparency and fairness.
• Utilize programming languages such as Python, Scala, or Java to develop scalable ML solutions and applications.

Benefits

Capital One offers a comprehensive benefits package designed to support the health, financial stability, and well-being of its employees. This includes competitive health insurance plans, retirement savings options, and wellness programs. Employees have access to ongoing professional development opportunities, including training, certifications, and industry conferences. The company promotes a flexible work environment, fostering work-life balance and inclusive culture. Additional benefits may include performance-based incentives, stock options, paid time off, and resources for financial planning. Capital One is dedicated to creating a workplace where employees can thrive, innovate, and grow their careers in a supportive environment.

Equal Opportunity

Capital One is an equal opportunity employer committed to fostering an inclusive environment for all employees and applicants. The company does not discriminate based on race, color, religion, national origin, gender, sexual orientation, gender identity, age, disability, or any other legally protected status. Capital One adheres to all applicable federal, state, and local laws regarding equal employment opportunity and non-discrimination. The organization also promotes a drug-free workplace and considers qualified applicants with criminal histories in accordance with relevant laws and regulations. All employment decisions are made based on merit, qualifications, and business needs, ensuring a fair and equitable hiring process for everyone.