onsite
MLOps AIOps Lead GCP - Iris Software
Software Engineer
Lead the design and deployment of end‑to‑end MLOps and AIOps pipelines on GCP, driving automation, scalability, and reliability for AI workloads.
About the role
Key Responsibilities
- Architect and implement MLOps and AIOps solutions on Google Cloud Platform, ensuring high availability and performance.
- Design CI/CD pipelines for model training, validation, and deployment using Kubernetes, Terraform, and Cloud Build.
- Collaborate with data scientists and DevOps teams to streamline model lifecycle management and monitoring.
- Implement observability, logging, and alerting for AI services using Cloud Monitoring and Stackdriver.
- Lead code reviews, mentor junior engineers, and promote best practices in cloud-native AI engineering.
Requirements
- 5+ years of experience in MLOps/AIOps with a strong focus on GCP services.
- Proficiency in Python, Kubernetes, Terraform, and CI/CD tooling.
- Hands‑on experience with AI/ML model deployment, monitoring, and scaling.
- Excellent problem‑solving skills and ability to work in a fast‑paced environment.
- Strong communication skills and a collaborative mindset.
Skills
mlopskubernetescicdpythonterraform