About the job
At Crusoe, we are on a mission to enhance the availability of energy and intelligence, creating the engine for an ambitious AI-driven world where creativity thrives without compromising on scale, speed, or sustainability.
Join Crusoe and become part of the AI revolution with sustainable technology. You will be at the forefront of innovation, driving impactful solutions and collaborating with a team dedicated to shaping responsible and transformative cloud infrastructure.
Role Overview:
Crusoe Cloud is looking for a Senior Solutions Engineer to partner with our key enterprise clients as they deploy AI/ML workloads on our state-of-the-art GPU infrastructure. This role is highly interactive and customer-focused, requiring extensive technical knowledge in Kubernetes, MLOps, and cloud architecture.
You will manage the entire deployment process, from conducting Proofs of Concept (PoCs) to optimizing workloads after the sale, acting as a vital technical liaison between our customers and engineering teams. Ideal candidates will have a passion for AI infrastructure, proficiency in containerized systems, and the ability to translate workloads seamlessly across different cloud environments.
Your Responsibilities:
Customer Enablement: Lead the technical onboarding and deployment of intricate AI/ML workloads, managing the PoC process through to post-sales optimization.
Kubernetes & MLOps Implementation: Design and deploy ML workloads utilizing Kubernetes-based frameworks (e.g., Ray, Kubeflow) to create infrastructure that optimally balances performance, scalability, and efficiency.
Infrastructure-Centric Approach: Move beyond abstract services, deploy and refine AI/ML workloads directly on Crusoe's infrastructure, ensuring optimum performance at both the container and hardware levels.
Cross-Cloud Migration: Assist customers in transitioning and adapting workloads across AWS, Azure, and GCP, articulating the trade-offs between cloud-native and Crusoe-native strategies.
Technical Communication: Conduct workshops, live demonstrations, and solution reviews, while contributing to case studies, solution briefs, and blog content that showcase real-world customer successes.
Customer Advocacy: Provide valuable feedback to internal engineering and product teams, helping to enhance Crusoe’s platform based on hands-on implementation experiences.
Qualifications:
Proven expertise in Kubernetes and MLOps, with hands-on experience in deploying and managing cloud-based infrastructure.
Strong understanding of AI/ML workloads and the ability to optimize them for performance and efficiency.
Excellent communication skills, capable of conveying complex technical concepts to diverse audiences.
Experience with cross-cloud architectures and migrations between AWS, Azure, and GCP.
A passion for innovative technology and a desire to drive meaningful change in the AI landscape.
