C
$175,000 – $250,000
Listed on Crusoe’s own careers site. You apply with them directly — we never stand between you and the employer.
What this role is
Crusoe seeks a senior solutions engineer to help enterprise customers deploy AI/ML workloads on their GPU infrastructure, serving as the technical bridge between customers and the engineering team. The role combines hands-on infrastructure work—building and optimizing Kubernetes-based systems—with customer engagement, technical storytelling, and feedback that shapes the platform.
Our summary, not Crusoe’s wording. The full posting is on their site.
Skills this role names
- Amazon Web Services (AWS)
- Apache Airflow
- Docker
- Helm
- Kubeflow
- Kubernetes
- Linux
- Microsoft Azure
- MLflow
- Power Platform CLI
- Terraform
- V-Ray
Log in to see which of these are already on your profile.
What they ask for
Required
- 7+ years building and deploying containerized workloads
- Deep Kubernetes expertise including Helm, Terraform, and Docker
- MLOps deployment experience with frameworks like Ray, MLflow, or Airflow on Kubernetes
- Hands-on cloud infrastructure knowledge across AWS, GCP, or Azure
- Strong Linux and CLI proficiency
- Customer-facing technical confidence and communication skills
Nice to have
- Experience with Ray, Kubeflow, or other distributed ML orchestration platforms
- Exposure to Slurm
- Multi-cloud deployment or migration experience, especially AWS to Crusoe transitions
- Content contributions such as tech talks, blogs, or public case studies