Applied Ai Ml Associate

1 week ago

Bengaluru Karnataka, India JPMorganChase Full time

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.

**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.

**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 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 AWS cloud and containerization technologies (e.g., Docker, Kubernetes).
- Experience with monitoring and logging tools (e.g., Prometheus, Grafana, ELK Stack).

**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.

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