Senior MLOps Engineer

About the role

As a Senior MLOps Engineer, you will design and operate the core infrastructure that powers an AI‑enabled enterprise platform. You will ensure that machine‑learning models move from research notebooks to reliable, secure, and cost‑effective production deployments at scale.

Key responsibilities

• Build and maintain model serving infrastructure for real‑time inference, batch processing, and LLM endpoints.
• Define and implement CI/CD pipelines that automate model packaging, testing, and deployment.
• Establish observability, monitoring, and alerting frameworks to guarantee reliability and performance.
• Develop infrastructure‑as‑code templates and security postures for enterprise‑grade AI workloads.
• Collaborate with data scientists and ML engineers to streamline model lifecycle workflows.
• Set architectural standards and internal tooling for future AI model deployments.

Required profile

• Proven experience in building and operating large‑scale MLOps platforms.
• Strong understanding of production‑grade AI systems, including security, scalability, and cost optimization.
• Ability to work in an early‑stage environment and define best practices.

Required skills

• MLOps
• CI/CD pipelines
• Model serving (real‑time inference, batch processing, LLM endpoints)
• Observability frameworks
• Infrastructure as code
• Security posture for AI workloads

What we offer

• Opportunity to shape the AI infrastructure of a fast‑growing enterprise technology company.
• Competitive compensation package.
• Collaborative environment with top‑tier data science and engineering talent.