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CrusoeCrusoeNew York, NY

Senior Staff Solutions Engineer (NYC)

Lead technical onboarding and deployment of AI/ML workloads on Crusoe's GPU infrastructure, guiding enterprise customers from PoC through post-sale optimization using Kubernetes and MLOps. Requires 7+ years of containerized workload experience and deep expertise in Kubernetes, MLOps frameworks, and multi-cloud infrastructure.

175k – 250k
On-site7+ YOESolutions Architecture

About the role

What You'll Be Working On

Customer Enablement

  • Lead technical onboarding and deployment of complex AI/ML workloads with strategic enterprise customers—owning the POC through to post-sales optimization

Kubernetes + MLOps Focus

  • Architect and deploy ML workloads using Kubernetes-based stacks (e.g., Ray, Kubeflow)
  • Design infrastructure that balances performance, scalability, and efficiency

Infrastructure-Centric Thinking

  • Deploy and optimize AI/ML workloads directly on Crusoe infrastructure
  • Ensure performance at the container and hardware level

Cross-Cloud Translation

  • Help customers migrate and adapt workloads across AWS, Azure, and GCP
  • Understand and explain tradeoffs between cloud-native and Crusoe-native approaches

Technical Storytelling

  • Conduct workshops, live demos, and solution reviews
  • Contribute to case studies, solution briefs, and blog posts highlighting real-world customer success

Voice of the Customer

  • Relay feedback to internal engineering and product teams to continuously improve Crusoe’s platform

What You'll Bring to the Team

  • 7+ years building and deploying containerized workloads with Kubernetes
  • Experience with Helm, Terraform, Docker, and multi-node orchestration
  • Demonstrated success deploying ML frameworks (e.g., Ray, MLflow, Airflow) on Kubernetes for inference and model training workflows
  • Familiarity with compute, storage, networking, and scaling in AWS, GCP, or Azure
  • Experience translating workloads across clouds is highly desirable
  • Able to navigate stakeholder conversations, gather requirements, lead technical engagements, and support customers in both pre- and post-sales environments
  • Strong Linux and CLI proficiency
  • Strong communication skills and eagerness to partner cross-functionally with Engineering, Product, and Sales

Bonus Points

  • Experience with Ray, Kubeflow, or other distributed ML orchestration platforms
  • Exposure to Slurm
  • Multi-cloud deployment or migration experience (especially AWS → Crusoe transitions)
  • Content contributions (tech talks, blogs, public case studies)

Benefits

  • Competitive compensation and equity packages
  • Restricted Stock Units
  • Paid time off, paid holidays & leave of absence programs
  • Comprehensive health, dental & vision insurance
  • Employer contributions to HSA account
  • Paid parental leave
  • Paid life insurance, short-term and long-term disability
  • Professional development & tuition reimbursement
  • Mental health & wellness support
  • Commuter benefits (parking & transit)
  • Cell phone stipend
  • 401(k) Retirement plan with company match up to 4% of salary
  • Volunteer time off
  • Global travel insurance & emergency assistance
  • Daily meals allowance

Skills

KubernetesHelmTerraformDockerRayMLflowAirflowAWSGCPAzureLinuxCliKubeflowSlurm
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