About this role
The team is seeking an experienced MLOps / Cloud Deployment Engineer to join their Digital Finance IT team, which is focused on scaling AI and agentic systems in production. This role is crucial for ensuring the deployment, reliability, observability, and operational scale of these systems within a regulated enterprise environment. This position emphasizes cloud and platform engineering with a strong MLOps/LLMOps focus, rather than model building.
Key Responsibilities:
- Own and manage CI/CD pipelines for ML models and GenAI systems.
- Ensure the reliability and performance of deployed systems in a production environment.
- Implement observability tools and practices to monitor system health and performance.
- Collaborate with data scientists and software engineers to streamline deployment processes.
- Maintain best practices for cloud infrastructure and deployment in a regulated setting.
- Troubleshoot and resolve operational issues related to ML and GenAI systems.
Required Skills & Qualifications:
- Proven experience in MLOps, cloud deployment, and platform engineering.
- Strong proficiency in cloud platforms such as AWS, Azure, or Google Cloud.
- Familiarity with CI/CD tools and practices, particularly in the context of machine learning.
- Knowledge of containerization technologies like Docker and orchestration tools like Kubernetes.
- Experience with monitoring and observability tools for production systems.
- Excellent problem-solving skills and ability to work in a fast-paced environment.
Experience:
- 5-8 years of relevant experience in MLOps or cloud deployment roles.
What we offer:
- Opportunity to work on cutting-edge AI and agentic systems.
- Collaborative and innovative work environment.
- Professional growth and development opportunities.
Applications are read by our talent team, usually within two working days.
If you look like a fit we will call you, and you will hear from us either way.