Crusoe-posted 2 days ago
Full-time • Mid Level
San Francisco, CA
501-1,000 employees

Crusoe's mission is to accelerate the abundance of energy and intelligence. We’re crafting the engine that powers a world where people can create ambitiously with AI — without sacrificing scale, speed, or sustainability. Be a part of the AI revolution with sustainable technology at Crusoe. Here, you'll drive meaningful innovation, make a tangible impact, and join a team that’s setting the pace for responsible, transformative cloud infrastructure. About the Role: Crusoe Cloud is seeking a Sr. to Senior Staff level Solutions Engineer to work closely with our most strategic enterprise customers deploying AI/ML workloads on Crusoe’s high-performance GPU infrastructure. This is a hands-on, customer-facing role requiring deep technical expertise in Kubernetes, MLOps, and cloud infrastructure. You’ll guide customers through end-to-end deployment—owning the PoC process, optimizing workloads post-sale, and serving as a critical technical voice between our customers and engineering teams. Ideal candidates are passionate about AI infrastructure, fluent in containerized environments, and confident translating workloads across cloud platforms.

  • Lead technical onboarding and deployment of complex AI/ML workloads with strategic enterprise customers—owning the POC through to post-sales optimization.
  • Architect and deploy ML workloads using Kubernetes-based stacks (e.g., Ray, Kubeflow)
  • Design infrastructure that balances performance, scalability, and efficiency.
  • Go beyond abstracted services—deploy and optimize AI/ML workloads directly on Crusoe infrastructure. Ensure performance at the container and hardware level.
  • Help customers migrate and adapt workloads across AWS, Azure, and GCP. Understand and explain the tradeoffs between cloud-native and Crusoe-native approaches.
  • Conduct workshops, live demos, and solution reviews. Contribute to case studies, solution briefs, and blog posts that highlight real-world customer success.
  • Relay feedback to internal engineering and product teams to continuously improve Crusoe’s platform based on real-world implementation experience.
  • Deep Kubernetes Expertise: 7+ years building and deploying containerized workloads. Experience with Helm, Terraform, Docker, and multi-node orchestration a must.
  • MLOps Deployment Experience: Demonstrated success deploying ML frameworks (e.g., Ray, MLflow, Airflow) on Kubernetes—especially for inference and model training workflows.
  • Hands-on Cloud Infrastructure Knowledge:Familiarity with compute, storage, networking, and scaling in AWS, GCP, or Azure. Experience translating workloads across clouds is highly desirable.
  • Customer-Facing Technical Confidence: 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:Comfortable operating in Linux environments and troubleshooting infrastructure issues via CLI.
  • Collaborative Energy: Strong communication skills and eagerness to partner cross-functionally with Engineering, Product, and Sales to make customers successful.
  • Experience with Ray, Kubeflow, or other distributed ML orchestration platforms
  • Exposure to Slurm, but with a primary focus on containerized MLOps over traditional HPC
  • Multi-cloud deployment or migration experience (especially AWS ➝ Crusoe transitions)
  • Content contributions (tech talks, blogs, public case studies)
  • Industry competitive pay
  • Restricted Stock Units in a fast growing, well-funded technology company
  • Health insurance package options that include HDHP and PPO, vision, and dental for you and your dependents
  • Employer contributions to HSA accounts
  • Paid Parental Leave
  • Paid life insurance, short-term and long-term disability
  • Teladoc
  • 401(k) with a 100% match up to 4% of salary
  • Generous paid time off and holiday schedule
  • Cell phone reimbursement
  • Tuition reimbursement
  • Subscription to the Calm app
  • MetLife Legal
  • Company paid commuter benefit; $300/month
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