Ml Ops Engineer

Job Summary

Were working with a Silicon Valleyorigin AI company focused on taking AI out of notebooks and into production.

This role sits at the intersection of machine learning infrastructure and reliability.

The team is responsible for making sure AI systems are deployable observable scalable and cost-efficient across cloud and hybrid environments.

If you enjoy turning models into real reliable systems this role is built for that.

What youll do

• Deploy and operate ML models in production environments
• Build and maintain CI/CD pipelines for ML workloads
• Manage model serving monitoring logging and alerting
• Work with backend and platform teams to productionize AI systems
• Improve reliability performance and cost efficiency of AI deployments

What were looking for

• Experience as an MLOps Engineer ML Engineer or Platform Engineer
• Strong understanding of Kubernetes containers and cloud infrastructure
• Experience with model deployment serving and monitoring
• Familiarity with CI/CD infrastructure-as-code and automation
• Comfortable owning production systems end-to-end

Nice to have

• Experience with on-prem or hybrid AI deployments
• Familiarity with model optimization inference performance or GPU workloads
• Experience working with large-scale AI or data platforms

Apply Now