About the role
AI Infrastructure Engineer (GPU) at a well-funded distributed-cloud startup, hired through Pragmatike.
The company builds next-generation AI-native cloud services: GPU-powered infrastructure for AI/ML workloads, secure storage and high-speed data transfer over a decentralized architecture that cuts the environmental impact of traditional cloud. This role owns the GPU infrastructure layer that runs those AI/ML workloads: provisioning, performance and reliability of GPU compute at scale. It suits an infrastructure engineer who understands GPUs, distributed systems and the demands of training and serving models.
Highlights
- Own the GPU infrastructure layer: provisioning, performance and reliability of GPU compute at scale
- For an infrastructure engineer who understands GPUs, distributed systems and training/serving models
- Fully remote within EMEA timezones, English required
- Differentiator: a greener, decentralized alternative to hyperscaler GPU cloud, built for AI-native workloads
This recap is dataskew's editorial summary, not the company's copy.