Senior Infrastructure Engineer (ML/AI)

Responsibilities

What does our ML/AI team do? The team supported a Generative AI solution for automation and integration.

Our Team: International Sr-level professionals from all over the Globe, experienced in building high-performing, scalable, enterprise-grade applications. Unique team of multinational professionals with integration, cloud, and consumer experience.

We are currently seeking a Senior Infrastructure Engineer with experience in the AI domain.

As a Senior Infrastructure Engineer, you will be responsible for deploying, scaling, and maintaining services for the ML/AI team. You will closely work with ML Engineers and Data Scientists as part of a small, flexible team and will have a direct impact on the modernization and maturation of the platform, including infrastructure architecture decisions.

Qualifications / Experience / Technical Skills

• BS/MS degree in Computer Science, Engineering or a related subject (or equivalent experience)
• 3-5 years professional experience in hands-on engineering roles (DevOps/SRE)
• 6+ months of experience with hosting AI models (ML flow, AWS SageMaker, Azure AI, Kubernetes) is preferred
• 6+ months of experience with ML Ops (ML flow, vector databases (Qdrant), Dagster) is preferred
• Kubernetes Expertise: Strong experience managing Kubernetes clusters and workloads, specifically using EKS (Elastic Kubernetes Service)

Soft Skills / Personal Characteristics

• Readiness to communicate in English with your colleagues

Workato is an equal opportunity employer. This job description reflects the responsibilities and qualifications for the role and is intended for recruitment purposes only. If you are interested in this role, please apply through the official channels.

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