AI Ops Engineer

TL;DR

AI Ops Engineer: Bridging the gap between Data Science and Operations, ensuring models are deployed reliably, scalably and securely with an accent on AI/MLOps, automation and building robust, high-performance infrastructure on the cloud. Focus on optimizing model deployment and inference speed.

Location: Warszawa, hybrid work model

Company

hirify.global is looking for an AI Ops Engineer.

What you will do

• Design, deploy, and maintain scalable ML infrastructure and pipelines for production AI systems.
• Implement AI/MLOps best practices, including model versioning, monitoring, and automated retraining workflows.
• Manage containerization and orchestration of AI workloads using Docker and Kubernetes.
• Set up and maintain CI/CD pipelines for machine learning models and data processing workflows.
• Monitor AI systems in production and track model performance using Prometheus, Grafana, and ELK stack.
• Collaborate with data scientists and engineers to optimize model deployment and inference speed.

Requirements

• Minimum 5 years in DevOps, MLOps, or infrastructure engineering with at least 2 years focused on AI/ML systems.
• Experience with MLflow, Kubeflow, Airflow, or similar platforms.
• Strong Python skills.
• Strong expertise in AWS, Azure, or GCP with hands-on experience in their ML services.
• Proficiency with Docker or Kubernetes.
• Expertise in Jenkins, GitLab CI, GitHub Actions or similar tools.