Lead Machine Learning Engineer - Python
Role summary
Capital One is seeking a Lead Machine Learning Engineer to design, develop, and deploy scalable ML solutions for complex business challenges. This role involves collaborating with cross-functional teams to translate innovative ideas into production-ready systems, shaping data-driven decision-making. The ideal candidate will have a strong background in ML and software engineering, with proven experience leading ML initiatives. Responsibilities include building and optimizing ML models, managing ML infrastructure, automating ML operations, and ensuring adherence to security and AI best practices.
About The Company
Capital One is a leading diversified bank renowned for its innovative approach to financial services. Committed to delivering exceptional customer experiences, Capital One leverages cutting-edge technology and data-driven strategies to provide a wide range of banking products, including credit cards, auto loans, and savings accounts. With a focus on digital transformation, the company continuously invests in advanced analytics, machine learning, and artificial intelligence to enhance operational efficiency and personalize customer interactions. As a socially responsible organization, Capital One emphasizes diversity, inclusion, and community engagement, fostering a dynamic workplace where innovation thrives.
About The Role
We are seeking a highly skilled Lead Machine Learning Engineer to join our dynamic technology team. In this pivotal role, you will be responsible for designing, developing, and deploying scalable machine learning solutions that address complex business challenges. You will work closely with cross-functional teams, including data scientists, data engineers, and product managers, to translate innovative ideas into production-ready systems. Your expertise will help shape the future of data-driven decision-making at Capital One, ensuring our machine learning applications are reliable, efficient, and aligned with industry best practices. The ideal candidate will be passionate about leveraging emerging technologies to solve real-world problems and will have a proven track record of leading ML initiatives in a fast-paced environment.
Qualifications
The ideal candidate will possess a strong educational background and extensive experience in machine learning and software engineering. Candidates should have a Bachelor's Degree in Computer Science, Electrical Engineering, Mathematics, or a related field. A minimum of 6 years of experience designing and building data-intensive solutions using distributed computing frameworks is required, with at least 4 years of programming experience in Python, Scala, or Java. Additionally, candidates should have at least 2 years of experience in building, scaling, and optimizing machine learning systems. Preferred qualifications include a Master’s or Doctoral degree, extensive experience with industry-recognized ML frameworks, and a background in developing production-grade data pipelines and deploying ML solutions in cloud environments such as AWS, Azure, or Google Cloud Platform.
Responsibilities
- Design, develop, and implement machine learning models and components that address real-world business problems in collaboration with product and data science teams.
- Make informed decisions regarding ML infrastructure by understanding modeling techniques, data selection, feature engineering, hyperparameter tuning, and model validation.
- Write, test, and optimize application code to automate model training, testing, deployment, and monitoring processes.
- Collaborate within Agile teams to create robust software solutions that enable advanced big data and machine learning applications.
- Maintain, retrain, and monitor models in production to ensure continued performance and relevance.
- Leverage cloud-based platforms and technologies to deliver scalable ML solutions, ensuring high availability and resilience.
- Construct and optimize data pipelines to efficiently feed ML models with high-quality data.
- Implement CI/CD practices, including automated testing and deployment, to streamline ML model lifecycle management.
- Ensure all code adheres to security standards, risk management policies, and best practices in Responsible and Explainable AI.
- Utilize programming languages such as Python, Scala, or Java to develop and maintain scalable ML systems.
Benefits
Capital One offers a comprehensive and competitive benefits package designed to support your overall well-being and professional growth. Employees have access to health insurance options, including medical, dental, and vision coverage, along with wellness programs and mental health resources. The company also provides financial benefits such as retirement plans, stock options, and performance-based incentives. Additional perks include paid time off, flexible work arrangements, professional development opportunities, and a collaborative work environment that encourages innovation. Capital One is committed to fostering an inclusive culture where diverse perspectives are valued and employees are empowered to succeed.
Equal Opportunity
Capital One is an equal opportunity employer committed to creating a diverse and inclusive 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 under applicable law. We promote a drug-free workplace and consider qualified applicants with criminal histories in accordance with relevant laws and regulations. We encourage all qualified individuals to apply and join our team, regardless of background or identity. If you require accommodations during the application process, please contact our recruiting team for assistance.