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.
About the job
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
Kubernetes, Helm, Terraform, Docker, Ray, MLflow, Airflow, AWS, GCP, Azure, Linux, Cli, Kubeflow, Slurm
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