
AI/ML Solutions Expert
3 hours ago
Job Summary:
We are seeking a seasoned Solutions Engineer to lead the deployment of AI/ML workloads on high-performance GPU infrastructure. This role requires expertise in Kubernetes, MLOps, and cloud infrastructure.
The successful candidate will have 3-5 years of experience building and deploying containerized workloads, as well as proficiency with Helm, Terraform, Docker, and multi-node orchestration.
Key Responsibilities:
- Technical Onboarding: Lead the technical onboarding and deployment of complex AI/ML workloads
- Kubernetes Focus: Architect and deploy ML workloads using Kubernetes-based stacks
- Infrastructure Expertise: Deploy and optimize AI/ML workloads directly on Crusoe infrastructure
- Cross-Cloud Migration: Assist customers in migrating and adapting workloads across AWS, Azure, and GCP
Requirements:
- Deep Kubernetes Knowledge: 3-5 years of experience building and deploying containerized workloads
- Experience with Helm, Terraform, Docker, and multi-node orchestration
- MLOps Deployment Experience: Demonstrated success deploying ML frameworks on Kubernetes
- Hands-on Cloud Infrastructure Expertise: Familiarity with compute, storage, networking, and scaling in AWS, GCP, or Azure
What We Offer:
- A competitive benefits package designed to support financial security, health, and overall well-being
- Salary or hourly compensation based on education, experience, knowledge, skills, and abilities
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