Location: Remote (EU)

Contract details: 12 months/freelance/SRL or PFA

Overview:

As a Senior MLOps Engineer, you will design, build, and optimize end-to-end machine learning operations infrastructure, enabling scalable agent deployment and lifecycle management across Databricks Mosaic AI.

Key Responsibilities:

• Architect and maintain ML operations pipelines for model training, deployment, and monitoring.

• Administer and optimize Databricks Mosaic AI platform and its AI agent ecosystem.

• Develop and manage MLflow lifecycle management, multi-agent orchestration, and agentic AI pipelines.

• Implement infrastructure automation using Kubernetes, Docker, and Terraform.

• Ensure observability using tools like Prometheus and Grafana.

• Develop and maintain CI/CD pipelines for ML models, data flows, and AI agents.

• Collaborate with Data Engineering and Platform teams to ensure compliance, security, and reliability.

Required Skills & Experience:

• Proven experience as MLOps Engineer or Platform Engineer (5+ years).

• Deep expertise with Databricks Mosaic AI, MLflow, and agentic AI orchestration.

• Advanced proficiency with Kubernetes, Docker, and Terraform.

• Experience building and maintaining CI/CD pipelines for ML systems.

• Strong knowledge of observability tools, monitoring, and AI governance principles.

• Solid understanding of data privacy, security, and responsible AI.

Nice to Have:

• Experience with LangChain, LlamaIndex, or multi-agent orchestration frameworks.

• Familiarity with Azure Databricks or AWS Sagemaker environments.