Machine learning Engineer
5+ years
United States
Full-time
Remote
1 month ago
About the role
About The Company
Capital One is a leading diversified bank known for its innovative approach to banking and financial services. With a commitment to leveraging technology and data-driven solutions, Capital One aims to deliver exceptional customer experiences while maintaining a focus on responsible banking practices. The company operates across various segments, including credit cards, auto loans, and savings accounts, and has established itself as a pioneer in digital banking transformation. Capital One's culture emphasizes continuous learning, collaboration, and innovation, fostering an environment where talented professionals can thrive and contribute to impactful projects that shape the future of financial services.
About The Role
As a Lead Machine Learning Engineer specializing in MLOps, KServe, and building Kubernetes clusters, you will play a pivotal role in advancing Capital One’s AI and machine learning capabilities. This position involves designing, developing, and deploying scalable machine learning solutions on cloud platforms such as AWS. You will work closely with cross-functional teams to productionize models, optimize data pipelines, and ensure high availability and performance of ML applications. Your expertise will contribute to building robust, automated, and efficient ML infrastructure, enabling the organization to deliver innovative financial products and services at scale. This role offers an exciting opportunity to lead complex projects, influence technical strategies, and stay at the forefront of AI engineering advancements.
Qualifications
The ideal candidate will possess a strong educational background and extensive experience in data engineering and machine learning. A minimum of a bachelor’s degree in computer science, electrical engineering, or a related field is required, with a preference for candidates holding a master's or doctoral degree. Candidates should have at least six years of experience designing and building data-intensive solutions utilizing distributed computing frameworks. Proficiency in programming languages such as Python, Scala, or Java is essential, with a minimum of four years of experience in this area. Additionally, candidates should have at least two years of experience in building, scaling, and optimizing ML systems, along with hands-on experience deploying solutions on cloud platforms like AWS, Azure, or Google Cloud. Strong knowledge of ML frameworks such as PyTorch, TensorFlow, or scikit-learn, along with experience in developing resilient data pipelines, is highly desirable. Leadership experience and a proven track record of developing production-ready ML solutions are also preferred qualifications.
Responsibilities
Benefits
Capital One offers a comprehensive benefits package designed to support the health, well-being, and financial security of its employees. Employees are eligible for competitive salaries, performance-based incentives, and long-term incentives where applicable. The company provides a range of health insurance options, including medical, dental, and vision plans, along with wellness programs and resources. Financial benefits include 401(k) retirement plans, employee stock purchase plans, and various savings programs. Capital One also promotes professional development through continuous learning opportunities, training programs, and support for industry certifications and conferences. The workplace culture emphasizes diversity, inclusion, and work-life balance, with flexible work arrangements and a supportive environment to foster career growth and personal well-being.
Equal Opportunity
Capital One is an equal opportunity employer committed to fostering an inclusive and diverse workplace. We do not discriminate based on race, color, religion, sex, national origin, age, disability, veteran status, sexual orientation, gender identity, or any other protected characteristic. We promote a culture of respect and fairness, ensuring all employees and applicants are treated with dignity and have equal access to opportunities for growth and advancement. Capital One complies with all applicable federal, state, and local laws regarding non-discrimination and equal employment opportunity. We encourage qualified individuals from all backgrounds to apply and join our team in shaping the future of financial technology.
Capital One is a leading diversified bank known for its innovative approach to banking and financial services. With a commitment to leveraging technology and data-driven solutions, Capital One aims to deliver exceptional customer experiences while maintaining a focus on responsible banking practices. The company operates across various segments, including credit cards, auto loans, and savings accounts, and has established itself as a pioneer in digital banking transformation. Capital One's culture emphasizes continuous learning, collaboration, and innovation, fostering an environment where talented professionals can thrive and contribute to impactful projects that shape the future of financial services.
About The Role
As a Lead Machine Learning Engineer specializing in MLOps, KServe, and building Kubernetes clusters, you will play a pivotal role in advancing Capital One’s AI and machine learning capabilities. This position involves designing, developing, and deploying scalable machine learning solutions on cloud platforms such as AWS. You will work closely with cross-functional teams to productionize models, optimize data pipelines, and ensure high availability and performance of ML applications. Your expertise will contribute to building robust, automated, and efficient ML infrastructure, enabling the organization to deliver innovative financial products and services at scale. This role offers an exciting opportunity to lead complex projects, influence technical strategies, and stay at the forefront of AI engineering advancements.
Qualifications
The ideal candidate will possess a strong educational background and extensive experience in data engineering and machine learning. A minimum of a bachelor’s degree in computer science, electrical engineering, or a related field is required, with a preference for candidates holding a master's or doctoral degree. Candidates should have at least six years of experience designing and building data-intensive solutions utilizing distributed computing frameworks. Proficiency in programming languages such as Python, Scala, or Java is essential, with a minimum of four years of experience in this area. Additionally, candidates should have at least two years of experience in building, scaling, and optimizing ML systems, along with hands-on experience deploying solutions on cloud platforms like AWS, Azure, or Google Cloud. Strong knowledge of ML frameworks such as PyTorch, TensorFlow, or scikit-learn, along with experience in developing resilient data pipelines, is highly desirable. Leadership experience and a proven track record of developing production-ready ML solutions are also preferred qualifications.
Responsibilities
- Design, develop, and deploy scalable machine learning models and components that address complex business challenges, collaborating with product and data science teams to ensure alignment with organizational goals.
- Make informed decisions regarding ML infrastructure by applying expertise in modeling techniques, data selection, feature engineering, hyperparameter tuning, and model validation.
- Write, test, and optimize application code to automate the training, deployment, and monitoring of ML models, ensuring high performance and reliability.
- Participate in cross-functional Agile teams to develop and enhance software solutions that support advanced big data and machine learning applications.
- Maintain, retrain, and monitor models in production environments, ensuring continuous performance and accuracy.
- Leverage cloud-based architectures and technologies to deliver ML models at scale, including constructing and optimizing data pipelines for efficient data flow.
- Implement best practices in CI/CD, including automated testing, deployment, and monitoring, to streamline ML workflows and reduce deployment risks.
- Ensure all code and models adhere to governance standards, including responsible AI practices, explainability, and risk management protocols.
- Utilize programming languages such as Python, Scala, or Java to develop robust ML solutions and infrastructure components.
- Lead efforts in building and scaling Kubernetes clusters and deploying ML models using KServe, ensuring high availability and fault tolerance.
Benefits
Capital One offers a comprehensive benefits package designed to support the health, well-being, and financial security of its employees. Employees are eligible for competitive salaries, performance-based incentives, and long-term incentives where applicable. The company provides a range of health insurance options, including medical, dental, and vision plans, along with wellness programs and resources. Financial benefits include 401(k) retirement plans, employee stock purchase plans, and various savings programs. Capital One also promotes professional development through continuous learning opportunities, training programs, and support for industry certifications and conferences. The workplace culture emphasizes diversity, inclusion, and work-life balance, with flexible work arrangements and a supportive environment to foster career growth and personal well-being.
Equal Opportunity
Capital One is an equal opportunity employer committed to fostering an inclusive and diverse workplace. We do not discriminate based on race, color, religion, sex, national origin, age, disability, veteran status, sexual orientation, gender identity, or any other protected characteristic. We promote a culture of respect and fairness, ensuring all employees and applicants are treated with dignity and have equal access to opportunities for growth and advancement. Capital One complies with all applicable federal, state, and local laws regarding non-discrimination and equal employment opportunity. We encourage qualified individuals from all backgrounds to apply and join our team in shaping the future of financial technology.