Applied AI Machine Learning Lead, Asset Management

Join . Morgan Asset & Wealth Management, a global leader in financial services, offering top-tier investment management and private banking solutions. We're seeking a software engineer with Python expertise and prior experience in utilizing LLMs. Our team is dedicated to providing strategic advice and products to prominent corporations, governments, and wealthy team members. We value diversity and inclusion, fostering long-term partnerships to help our clients achieve their goals. Be part of our expansion of LLM use cases across business areas, and contribute to our mission of serving clients in a first-class way.

As an Applied AI Machine Learning Lead within Asset Management, you will have the opportunity to collaborate closely with various teams to prototype, build, test, and deploy a large scale federated LLM platform. You will be part of an agile team focused on delivering trusted, market-leading technology products in a secure, stable, and scalable way. This role provides the chance to partner with our Global Data Science teams to design, develop, deploy, and operate machine learning promoten applications and data pipelines..

Job responsibilities
Handling 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. 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, and 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.