You’re ready to gain the skills and experience needed to grow within your role and advance your career — and we have the perfect Applied AI ML opportunity for you.

 

As a Applied AI ML Associate at JPMorgan Chase within the Commercial and Investment Banking, you'll be an integral part of an agile team that works to enhance, build, and deliver trusted market-leading technology products in a secure, stable, and scalable way. As a core technical contributor, you are responsible for conducting critical technology solutions across multiple technical areas within various business functions in support of the firm’s business objectives. You will be working with cutting-edge technologies to ensure scalable, reliable, and efficient AI solutions. 

 

Job Responsibilities : 

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 in AWS, 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.Identifies opportunities to eliminate or automate remediation of recurring issues to improve overall operational stability of software applications and systems

 

Required qualifications, capabilities, and skills :

Formal Training or certification on Machine Learning concepts and 2+ years applied experience.Strong expertise in deploying and managing machine learning models in production environmentsAdvanced Python Programming Skills including Pandas, Numpy and Scikit- LearnProficiency in building and maintaining CI/CD pipelines for machine learning workflows.Proficient in all aspects of the Software Development Life CycleAdvanced understanding of agile methodologies such as CI/CD, Application Resiliency, and SecurityDemonstrated proficiency in software applications and technical processes within a technical discipline (e.g., cloud, artificial intelligence, machine learning, mobile, etc.)Expertise in AWS cloud and containerization technologies (e.g., Docker, Kubernetes).Experience with monitoring and logging tools (e.g., Prometheus, Grafana, ELK Stack).Excellent problem-solving skills and attention to detail and Strong communication skills to collaborate effectively with cross-functional teams.Hands-on practical experience delivering system design, application development, testing, and operational stability

 

Preferred qualifications, capabilities, and skills :

Proven experience in deploying and managing machine learning models in production environments.Strong ability to monitor ML models in production, addressing model performance and data quality issues effectively.Working knowledge of security best practices and compliance standards for Machine Learning systems.Experience with infrastructure optimization techniques to enhance performance and efficiency.Development of REST APIs using frameworks such as Flask or FastAPI for seamless integration into business solutions.