Machine Learning Engineering / Applied AI ML Lead - Asset Management Research Technology

JP Morgan

Location: Greater London

Job Type: Full time

Posted


JP Morgan Asset Management is expanding LLM use cases across AM business areas. We are seeking a software engineer with expertise in python and prior experience in utilizing LLMs. As an 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.
  • Add to team culture of diversity, equity, inclusion, and respect.

Required qualifications, capabilities, and skills

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

Preferred qualifications, capabilities, and skills

  • Experience with financial data and data science.