AI Infrastructure Engineer
Builds and runs end-to-end ML inference infrastructure for generative AI image models across mobile and web platforms. Requires expertise in distributed systems, Kubernetes, Kafka, Redis, GPUs, and multi-cloud environments.
About the job
Responsibilities
- Design, implement and run next-generation inference architecture for running models powering all platforms and applications (mobile, web, etc.).
- Work alongside fast-paced team developing state-of-the-art image generation models serving over 16 million users.
Requirements
- Experience with large distributed systems.
- Familiarity with K8S, Kafka, NATS, Redis, etc.
- Experience with on-prem and multi-cloud clusters.
- Deep understanding of tradeoffs and failure modes of systems.
- Excellent understanding of GPUs handling large workloads.
- Experience deploying or optimizing GPU workloads end-to-end is a huge plus.
- Comfortable working on small, fast-paced teams.
Nice-to-Haves
- Passion for anime aesthetic.
Skills
Kubernetes, Kafka, Nats, Redis, GPU, Distributed Systems, Multi-Cloud, Inference Architecture
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