JP Morgan Asset Management is expanding Large Language Model (LLM) use cases across Asset Management business areas. We are seeking a software engineer with expertise in python and prior experience in utilizing LLMs. 

As a Large Language Model (LLM) Engineering Lead within Asset Management, you will be collaborating closely with various teams to prototype, build, test and deploy a large scale federated LLM platform. You will work with an agile team that will work on building, and delivering trusted market-leading technology products in a secure, stable, and scalable way. You will partner with our Global Data Science teams to design, develop, deploy and operate machine learning driven applications and data pipelines.

 

Job responsibilities

Hands on involvement in building and operating highly sophisticated LLM driven applications. Partnering directly with other technology teams on LLM projects to advise and assist as needed. Collaborating with Data Science, Cybersecurity to deliver state of the art ML products. Managing and supporting a team of ML and MLOps engineers. Collaborating with Devops engineers to plan and deploy data storage and processing systems, Executing 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. Developing secure high-quality production code, and reviews and debugs code written by others.

 

Required qualifications, capabilities, and skills

Degree in a computer science or related discipline. Formal training or certification on software engineering concepts and advanced applied experience. Advanced python programming skills. Proven experience in building and operating scalable ML-driven products. Hands on experience and certifications in Azure or AWS (Architect, Big Data, AI/ML). Proficiency with cloud technologies like Kubernetes or Airflow. Experience working in a highly regulated environment. Proficient in all aspects of the Software Development Life Cycle. Familiarity with Terraform or IaaC. Ability to design and deliver large scale cloud-native architectures. Expertise in microservices performance tuning, performance optimization, and real-time applications.

 

Preferred qualifications, capabilities, and skills

Experience with financial data and data science.