DescriptionJP 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
- Participate 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.
