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Senior Staff Solutions Engineer (NYC)
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Crusoe Energy·Denver, CO - US·26 мая

Senior Staff Solutions Engineer (NYC)

🏢 ОфисSeniorПолная занятость
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Наша компания

Crusoe is on a mission to accelerate the abundance of energy and intelligence. As the only vertically integrated AI infrastructure company built from the ground up, we own and operate each layer of the stack — from electrons to tokens — to power the world's most ambitious AI workloads. When you join Crusoe, you join a team that is building the future, faster. We're in the midst of the greatest industrial revolution of our time. The demand for AI compute is boundless, and power is a bottleneck. We're solving that — with an energy-first approach that makes AI infrastructure better for the world

О роли

We're looking for problem-solving, opportunity-finding teammates with a sense of urgency, who believe in the scale of our ambition and thrive on a path not fully paved — people who want to grow their careers alongside a team of experts across energy, manufacturing, data center construction, and cloud services. If you want to do the most meaningful work of your career, help our customers and partne

Чем предстоит заниматься

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 in translating workloads across cloud platforms

Наши требования

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)

Мы предлагаем

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
Additional perks & programs specific to location
Compensation will be paid in the range of up to $175,000 - $250,000 + 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

Дополнительно

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
C
Crusoe Energy
Denver, CO - US

ГрейдSenior
ЗанятостьПолная занятость
РегионСША
ФорматОфис
ИсточникСкрыто
Опубликовано26 мая
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