Infrastructure Engineer
Role summary
Maxana is seeking an experienced Infrastructure Engineer for a fast-growing AI company. This role focuses on building and maintaining the platform layer for large-scale ML training, inference, and deployment. The engineer will work with GPU, compute, distributed systems, and cloud-native platforms (AWS, GCP, Azure, Docker, Kubernetes). Key responsibilities include improving reliability, observability, and performance, owning production reliability end-to-end, and developing internal tooling. Familiarity with ML infrastructure is a plus. The position offers a competitive salary and benefits.
Maxana is seeking an experienced Infrastructure Engineer for a confidential client — a fast-growing AI company. In this role you will build and maintain the platform layer supporting large-scale ML training, inference, and deployment. This is a high-impact role at the intersection of cloud infrastructure and ML systems.
Key Responsibilities
- Build and maintain infrastructure supporting large-scale ML training and inference workloads
- Work with GPU and compute infrastructure, distributed systems, and cloud-native platforms
- Improve reliability, observability, and performance across the platform layer
- Collaborate directly with senior engineers and product teams on architecture decisions
- Own production reliability — monitoring, incident response, and proactive risk reduction
- Develop and maintain internal tooling and automation to support engineering operations
### Requirements
- 5+ years of infrastructure or platform engineering experience in a production environment
- Strong distributed systems background — experience with large-scale compute workloads preferred
- Cloud-native infrastructure experience — AWS, GCP, or Azure; Docker and Kubernetes required
- Familiarity with ML infrastructure a strong plus — training pipelines, inference serving, GPU workloads
- Experience owning production reliability end to end
### Benefits
- Competitive base salary ($130,000-$240,000) + equity
- Medical, dental, and vision
- Flexible paid time off
- Learning and development stipend
- Working at the forefront of AI infrastructure at scale
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