REQUIREMENTS

7+ years of experience in Machine Learning Engineering or MLOps
3+ years designing production-grade MLOps platforms
Experience with LLM deployment and operationalization
Strong knowledge of MLflow, Kubeflow, Vertex AI, Azure ML, SageMaker or similar platforms
Experience deploying GenAI applications in enterprise environments
Knowledge of RAG architectures, vector databases, model evaluation, and prompt management
Experience with Kubernetes, Docker, CI/CD pipelines
Familiarity with GPU infrastructure
Strong understanding of AI governance and model lifecycle management
Upper-Intermediate or higher level of English

RESPONSIBILITIES

• Design enterprise MLOps and LLMOps architecture
• Build deployment strategies for AI and LLM solutions
• Define model lifecycle management processes
• Implement monitoring, observability, and evaluation frameworks
• Design CI/CD pipelines for machine learning workloads
• Collaborate with AI researchers, platform engineers, and DevOps teams
• Support AI governance and security requirements
• Advise client stakeholders on operational AI best practices