Machine Learning Engineer -Python
Role summary
Capital One is seeking a Lead Machine Learning Engineer to design, develop, and deploy production-ready ML solutions. This role involves creating scalable ML models and systems to address business challenges, working within an agile team. Responsibilities include building and maintaining cloud-based data pipelines, deploying models at scale, and ensuring optimal performance through monitoring and retraining. The position requires strong programming skills in Python, Scala, or Java, expertise in ML architecture, and experience with distributed computing frameworks. The ideal candidate will have at least six years of professional experience in data-intensive solutions and two years in developing and scaling ML systems, with a Bachelor's degree in a related field.
About The Company
Capital One is a leading diversified financial services company renowned for its innovative approach to banking and credit card services. With a strong emphasis on technology-driven solutions, Capital One aims to deliver exceptional customer experiences through digital innovation, data analytics, and responsible banking practices. The company operates across various segments, including credit cards, auto loans, savings accounts, and small business banking, serving millions of customers nationwide and globally. Capital One's commitment to fostering a dynamic, inclusive, and forward-thinking workplace has established it as a trusted leader in the financial industry.
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. As part of an agile, collaborative team, you will be responsible for designing, developing, and deploying sophisticated ML models and systems that address complex business challenges. This role requires a deep understanding of ML architecture, extensive programming expertise, and experience in cloud-based data pipelines. You will work closely with data scientists, product managers, and operations teams to ensure the seamless integration and continuous improvement of machine learning applications, ultimately enabling Capital One to enhance its products, services, and customer engagement strategies.
Qualifications
The ideal candidate will possess a strong educational background with a Bachelor's Degree in computer science, electrical engineering, mathematics, or a related field. Candidates should have a minimum of six years of professional experience in designing and building large-scale, data-intensive solutions utilizing distributed computing frameworks. Proficiency in programming languages such as Python, Scala, or Java is essential, with at least four years of hands-on experience. Additionally, candidates should demonstrate at least two years of experience in developing, scaling, and optimizing machine learning systems. Preferred qualifications include advanced degrees (Master’s or Doctorate), extensive experience with industry-recognized ML frameworks like TensorFlow or PyTorch, and a proven track record of deploying ML solutions in cloud environments such as AWS, Azure, or Google Cloud Platform. Leadership experience in managing teams and contributing to industry innovations through publications or open-source projects is highly valued.
Responsibilities
The Lead Machine Learning Engineer will be responsible for a broad spectrum of activities, including but not limited to designing and delivering machine learning models that solve real-world business problems in collaboration with product and data science teams. You will inform infrastructure decisions based on your understanding of ML modeling techniques, data quality, feature engineering, and validation processes. Developing and maintaining scalable, automated data pipelines to support ML workflows is a key aspect of the role. You will also be tasked with retraining, monitoring, and maintaining models in production environments to ensure optimal performance. Leveraging cloud platforms and architectures to deploy models at scale, you will build and optimize data pipelines that feed ML models, ensuring resilience and efficiency. The role demands adherence to best practices in software development, including continuous integration and deployment, automated testing, and rigorous model governance to uphold responsible and explainable AI standards. You will write robust, maintainable code in Python, Scala, or Java, and collaborate within cross-functional agile teams to create innovative solutions that leverage big data and machine learning technologies.
Benefits
Capital One offers a comprehensive benefits package designed to support the health, financial security, and overall well-being of its employees. Benefits include competitive health insurance plans, retirement savings options, paid time off, and wellness programs. The company also provides opportunities for professional development, continuous learning, and career advancement. Additionally, employees may be eligible for performance-based incentives, including cash bonuses and long-term incentives, depending on individual and company performance. Capital One fosters an inclusive workplace culture that values diversity and promotes work-life balance, ensuring employees feel supported and empowered to succeed both professionally and personally.
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, sex, national origin, age, disability, veteran status, or any other protected characteristic in accordance with applicable federal, state, and local laws. Capital One also promotes a drug-free workplace and considers qualified applicants with criminal histories in a manner consistent with relevant laws and regulations. The company values diversity and is dedicated to creating a welcoming and equitable workplace where everyone can thrive.