Crusoe Cloud seeks a Senior Staff Solutions Engineer to lead deployment of AI/ML workloads on their high-performance GPU infrastructure. The role involves customer-facing technical onboarding, Kubernetes/MLOps architecture, and cross-cloud migration. Candidates need deep expertise in Kubernetes, MLOps, and cloud infrastructure.
Responsibilities
Lead technical onboarding and deployment of complex AI/ML workloads with strategic enterprise customers
Architect and deploy ML workloads using Kubernetes-based stacks (e.g., Ray, Kubeflow)
Optimize AI/ML workloads directly on Crusoe infrastructure at container and hardware level
Help customers migrate workloads across AWS, Azure, and GCP
Conduct workshops, live demos, and solution reviews
Relay customer feedback to engineering and product teams
Requirements
7+ years building and deploying containerized workloads with Kubernetes, Helm, Terraform, Docker
Demonstrated success deploying ML frameworks (Ray, MLflow, Airflow) on Kubernetes
Hands-on cloud infrastructure knowledge (AWS, GCP, or Azure)
Crusoe is an AI factory company focused on accelerating energy and intelligence abundance. They provide next-generation AI infrastructure and cloud compute solutions by deploying AI-optimized data centers and utilizing an energy-first approach.
Experience with Ray, Kubeflow, or distributed ML orchestration platforms
Exposure to Slurm
Multi-cloud deployment or migration experience
Content contributions (tech talks, blogs, public case studies)
Benefits
Equity / stock optionspaid time offHealth insurancedental insurancevision insuranceParental leavelife insurancedisability insuranceprofessional developmentcommuter benefitsretirement planmental health supportvolunteer time off