11 months ago
Dublin, IrelandSenior / Staff+
Responsibilities
- Lead technical onboarding and deployment of AI/ML workloads with enterprise customers.
- Own the proof of concept process and optimize workloads post-sale.
- Architect and deploy ML workloads using Kubernetes-based stacks.
- Deploy and optimize AI/ML workloads directly on Crusoe infrastructure.
- Assist customers in migrating and adapting workloads across AWS, Azure, and GCP.
- Conduct workshops, live demos, and solution reviews to showcase customer success.
- Relay customer feedback to internal engineering and product teams.
Requirements
- 3-5 years of experience building and deploying containerized workloads with Kubernetes.
- Demonstrated success deploying ML frameworks on Kubernetes for inference and model training.
- Familiarity with cloud infrastructure, including compute, storage, and networking in AWS, GCP, or Azure.
- Strong customer-facing technical skills to lead engagements and gather requirements.
- Proficiency in Linux environments and troubleshooting via CLI.
- Excellent communication skills and a collaborative mindset.
Benefits
- Competitive benefits package including pension contributions.
- Private health and dental insurance.
- Income protection and life assurance.