ML Cloud DevOps Lead — Azure & AWS

LSEG; St. Louis (MO); On-site; USD 108,000 - 162,000; Full time

Job summary

London Stock Exchange Group (LSEG) is seeking a Machine Learning DevOPS Engineer for the Cloud Products Framework. You will evangelize cloud product strategies, enable ML capabilities, and drive adoption of Azure and AWS across the organization.

You will mentor teams, design scalable cloud solutions, build ML models, and ensure robust, secure deployments. This role combines leadership with hands-on delivery in a fast-paced, open environment.

Qualifications

• A degree in Computer Science, Engineering or equivalent.
• Strong IaC understanding.
• Cloud experience with Azure and AWS.
• Proven ML solutions leadership or development.
• DevOps practices with ML deployment.
• Hands-on with Docker, CI/CD, secrets management, and programming languages (Java/JS, C#, Python).
• Experience with GitHub or GitLab.
• Strong architectural thinking and communication.
• Agile/Scrum experience.

Responsibilities

• Provide direction and mentoring on design and development.
• Create and implement technical solution designs and resolve issues.
• Support technical roadmaps for timely implementation of a technical solution strategy.
• Develop technical strategy and research to scale ML cloud product capabilities on Azure and AWS.
• Design, build, and deliver ML models and components for internal use cases.
• Inform ML infrastructure decisions including model choice, data, and training.
• Evaluate new technologies and lead development of standard reference code.
• Build strong relationships with internal and external customers and teams.
• Communicate complex technical information clearly to stakeholders.

Skills

Azure

AWS

DevOps

ML deployment

CI/CD

Docker

Python

Java

C#

JavaScript

GitHub

GitLab

Education

B.S. in Computer Science or related

Tools

GitHub

GitLab

Job description

London Stock Exchange Group (LSEG) is seeking a Machine Learning DevOPS Engineer for the Cloud Products Framework. You will evangelize cloud product strategies, enable ML capabilities, and drive adoption of Azure and AWS across the organization.

You will mentor teams, design scalable cloud solutions, build ML models, and ensure robust, secure deployments. This role combines leadership with hands-on delivery in a fast-paced, open environment.