Senior MLOps Engineer

About the role

As a Senior MLOps Engineer, you will shape the core AI infrastructure of an enterprise technology platform that delivers real‑time recommendations, automation and natural‑language interfaces. You will be responsible for turning experimental models into reliable, secure, and cost‑efficient production services for mission‑critical customers.

Key responsibilities

• Design and build model serving infrastructure for real‑time inference, batch processing and LLM endpoints.
• Implement CI/CD pipelines that automate the end‑to‑end model lifecycle.
• Establish observability frameworks and evaluation systems to monitor performance and reliability.
• Define architectural standards, deployment patterns and internal tooling for the early‑stage platform.
• Collaborate with data scientists and ML engineers to streamline workflows and enforce best practices.

Required profile

• Proven experience in building and operating production‑grade MLOps systems.
• Strong understanding of reliability, security and scalability requirements for enterprise AI workloads.
• Ability to translate research prototypes into robust, maintainable services.

Required skills

• CI/CD pipeline development
• Model serving and inference engineering
• Observability and monitoring frameworks
• Infrastructure as code practices