Staff Solutions Engineer

21 Days Old

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Find out more about this role by reading the information below, then apply to be considered.
Be 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 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: 5-7 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.
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 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; $200/month
Compensation Range
Compensation will be paid in the range of up to $215,000 -$250,000 per year + Bonus. Restricted Stock Units are included in all offers. Compensation to be determined by the applicants knowledge, education, and abilities, as well as internal equity and alignment with market data.
Crusoe is an Equal Opportunity Employer. Employment decisions are made without regard to race, color, religion, disability, genetic information, pregnancy, citizenship, marital status, sex/gender, sexual preference/ orientation, gender identity, age, veteran status, national origin, or any other status protected by law or regulation.Seniority level Seniority levelMid-Senior level Employment type Employment typeFull-time Job function Job functionEngineering and Information Technology IndustriesTechnology, Information and Internet Referrals increase your chances of interviewing at Crusoe by 2x Get notified about new Solutions Engineer jobs in San Francisco, CA . San Mateo, CA $115,000 - $165,000 3 days ago San Francisco, CA $100,000 - $130,000 2 weeks ago San Francisco, CA $160,000 - $200,000 3 days ago San Francisco, CA $120,000 - $180,000 6 months ago Foster City, CA $120,000.00 - $160,000.00 1 week ago San Francisco, CA $130,000.00 - $140,000.00 2 weeks ago San Francisco, CA $135,000.00 - $170,000.00 4 months ago San Francisco, CA $180,000.00 - $200,000.00 4 weeks ago San Mateo, CA $131,800.00 - $214,200.00 2 days ago Hayward, CA $100,000.00 - $150,000.00 5 months ago San Francisco, CA $125,000.00 - $175,000.00 3 weeks ago San Francisco, CA $150,000.00 - $180,000.00 4 months ago San Francisco, CA $160,000.00 - $220,000.00 2 weeks ago San Francisco, CA $100,000.00 - $220,000.00 3 months ago Redwood City, CA $120,000.00 - $158,000.00 2 weeks ago San Francisco, CA $150,000.00 - $200,000.00 7 months ago San Francisco, CA $140,000.00 - $180,000.00 2 months ago San Francisco, CA $220,900.00 - $292,400.00 3 days ago San Francisco, CA $35,000 - $180,400 1 month ago San Francisco, CA $160,000 - $240,000 3 months ago We’re unlocking community knowledge in a new way. Experts add insights directly into each article, started with the help of AI.
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Location:
San Francisco, CA
Salary:
$200

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