JPMorgan Chase is seeking a Lead Software Engineer to enhance, build, and deliver trusted market-leading technology products in a secure, stable, and scalable way, with a focus on deploying, monitoring, and managing machine learning models in production environments.
Requirements
- Formal Training or certification on Machine Learning concepts and 5+ years applied experience.
- Strong expertise in deploying and managing machine learning models in production environments
- Advanced Python Programming Skills including Pandas, Numpy and Scikit- Learn
- Proficiency in building and maintaining CI/CD pipelines for machine learning workflows.
- Proficient in all aspects of the Software Development Life Cycle
- Advanced understanding of agile methodologies such as CI/CD, Application Resiliency, and Security
- Expertise in cloud platforms (e.g., AWS, Google Cloud, Azure) and containerization technologies (e.g., Docker, Kubernetes).
Responsibilities
- Collaborate with cross-functional teams, including data scientists and software engineers, to understand model requirements and integrate them into applications.
- Develop and implement strategies for deploying machine learning models into production, ensuring scalability, reliability, and efficiency.
- Design and maintain continuous integration and continuous deployment (CI/CD) pipelines to automate the testing, deployment, and updating of machine learning models.
- Manage and optimize the infrastructure required for running machine learning models, including cloud services, containerization (e.g., Docker), and orchestration tools (e.g., Kubernetes).
- Implement monitoring and logging solutions to track model performance, detect anomalies, and ensure models are operating as expected in production.
- Maintain version control for models and data, ensuring traceability and compliance with governance policies and ensure that deployed models adhere to security best practices and comply with relevant regulations and standards.
- Executes creative software solutions, design, development, and technical troubleshooting with ability to think beyond routine or conventional approaches to build solutions or break down technical problems
Other
- Bachelor's degree in Computer Science, Engineering, or a related field, with relevant experience in ML Ops or related roles.
- Excellent problem-solving skills and attention to detail
- Strong communication skills to collaborate effectively with cross-functional teams.
- Hands-on practical experience delivering system design, application development, testing, and operational stability
- Ability to work in a team and collaborate with cross-functional teams
