Senior Solutions Engineer - AI Infra & MLOps

Crusoe; United States; On-site; USD 175,000 - 250,000; Full time

Benefits offered by this job

Competitive compensation

Equity packages

Paid time off and holidays

Health, dental & vision insurance

HSA contributions

Parental leave

Life insurance & disability

Professional development

Mental health support

Commuter benefits

Cell phone stipend

401(k) with company match

Volunteer time off

Global travel insurance

Daily meals allowance

Location-specific perks

Job summary

Crusoe is seeking a Sr. to Senior Staff level Solutions Engineer to work with enterprise customers deploying AI/ML workloads on Crusoe’s GPU infrastructure. This role is hands-on and customer-facing, requiring deep expertise in Kubernetes, MLOps, and cloud infrastructure.

You’ll own the PoC, optimize workloads post-sale, and act as a technical voice between customers and engineering teams. Ideal candidates are fluent in containerized environments and can translate workloads across clouds.

Qualifications

• 7+ years building and deploying containerized workloads on Kubernetes.
• Deployment of ML frameworks (Ray, MLflow, Airflow) on Kubernetes for inference and training.
• Hands-on cloud infrastructure knowledge across compute, storage, and networking (AWS, GCP, Azure).
• Excellent customer-facing technical communication to gather requirements and lead engagements.
• Strong Linux/CLI proficiency for troubleshooting and ops tasks.
• Collaborative, cross-functional mindset with Engineering, Product, and Sales.

Responsibilities

• Lead technical onboarding and deployment of complex AI/ML workloads for strategic enterprise customers—from POC to post-sales optimization.
• Architect and deploy ML workloads using Kubernetes-based stacks (Ray, Kubeflow); design infrastructure for performance and efficiency.
• Deploy and optimize AI/ML workloads directly on Crusoe infrastructure across container and hardware levels.
• Assist customers in migrating workloads across AWS, Azure, and GCP; explain tradeoffs between cloud-native and Crusoe-native approaches.
• Conduct workshops, live demos, and solution reviews; contribute to case studies and blogs.
• Relay customer feedback to engineering and product teams to improve Crusoe’s platform.

Skills

Kubernetes expertise

MLOps deployment

Cloud infrastructure

Customer-facing communication

Linux proficiency

Cross-functional collaboration

Tools

Docker

Helm

Terraform

Ray

Kubeflow

MLflow

Airflow

Job description

Crusoe is seeking a Sr. to Senior Staff level Solutions Engineer to work with enterprise customers deploying AI/ML workloads on Crusoe’s GPU infrastructure. This role is hands-on and customer-facing, requiring deep expertise in Kubernetes, MLOps, and cloud infrastructure.

You’ll own the PoC, optimize workloads post-sale, and act as a technical voice between customers and engineering teams. Ideal candidates are fluent in containerized environments and can translate workloads across clouds.