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Senior to Senior Solutions Engineer

Job in San Francisco, San Francisco County, California, 94199, USA
Listing for: Epoch Biodesign
Full Time position
Listed on 2025-12-05
Job specializations:
  • IT/Tech
    Cloud Computing, AI Engineer
Job Description & How to Apply Below
Position: Senior to Senior Staff Solutions Engineer

Crusoe is building the World’s Favorite AI‑first Cloud infrastructure company. We’re pioneering vertically integrated, purpose‑built AI infrastructure solutions trusted by Fortune 500 companies to power their most advanced AI applications. Crusoe is redefining AI cloud infrastructure, with a mission to align the future of computing with the future of the climate. Our AI platform is recognized as the "gold standard" for reliability and performance.

Our data centers are optimized for AI workloads and are powered by clean, renewable energy.

Be part of the AI revolution with sustainable technology e, 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 Staff 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.

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:
    Go beyond abstracted services—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 the 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 that highlight real‑world customer success.

  • Voice of the Customer:
    Relay feedback to internal engineering and product teams to continuously improve Crusoe’s platform based on real‑world implementation experience.

What You’ll Bring to the Team
  • Deep Kubernetes Expertise: 3‑5 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.

Bonus Points
  • 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

Benefits
  • Hybrid work schedule

  • 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…

Position Requirements
10+ Years work experience
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