Strategic AI/ML Workload Engineer

1 week ago

Dublin, Dublin City, Ireland beBeeSolutions Full time €80,000 - €160,000

Unlock the future of computing with a forward-thinking Solutions Engineer role. This is a hands-on, customer-facing position requiring deep technical expertise in Kubernetes, MLOps, and cloud infrastructure.

Key Responsibilities:

  • Lead technical onboarding and deployment of complex AI/ML workloads with strategic enterprise customers.
  • Architect and deploy ML workloads using Kubernetes-based stacks, ensuring performance, scalability, and efficiency.
  • Deploy and optimize AI/ML workloads directly on our infrastructure, balancing performance at the container and hardware level.
  • Help customers migrate and adapt workloads across AWS, Azure, and GCP, understanding tradeoffs between cloud-native and our native approaches.

Requirements:

  • Deep Kubernetes Expertise: 3-5 years building and deploying containerized workloads, experience with Helm, Terraform, Docker, and multi-node orchestration required.
  • MLOps Deployment Experience: Demonstrated success deploying ML frameworks on Kubernetes for inference and model training workflows.
  • Hands-on Cloud Infrastructure Knowledge: Familiarity with compute, storage, networking, and scaling in AWS, GCP, or Azure, with experience translating workloads across clouds highly desirable.
  • Customer-Facing Technical Confidence: Ability to navigate stakeholder conversations, gather requirements, lead technical engagements, and support customers in pre- and post-sales environments.
  • Strong Linux and CLI Proficiency: Comfortable operating in Linux environments and troubleshooting infrastructure issues via CLI.

What We Offer:

  • A competitive benefits package supporting financial security, health, and overall well-being.
  • Compensation will be paid as salary or hourly, based on education, experience, knowledge, skills, and abilities, as well as internal equity and market data alignment.

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