Push massive compute clusters to their limits. You will be a core contributor to a novel container orchestration platform built in-house by our team to scale far beyond what’s possible with systems like Kubernetes.
Develop and maintain FastAPI and gRPC APIs that serve as the interface for our agentic infrastructure used both in training and production.
Use Terraform to stand up and evolve complex infrastructure for both research and production.
Collaborate with research teams to stand up and optimize systems for novel AI training runs and experimental applications.
Requirements
Have deep experience working on large-scale machine learning infrastructure. You know how to reason about training at scale, identifying bottlenecks and engineering solutions to optimize system performance in training environments.
Know how to build new things from 0-1 quickly, and then scale them 1,000,000x.
Have a keen eye for performance and optimization. You know how to squeeze the most performance out of complex, globally-distributed systems.
Know your way around cloud platforms and work with infrastructure-as-code tech like Terraform.
Are driven by solving complex, ambiguous problems at the intersection of infrastructure scalability, virtualization efficiency, and agentic capabilities.
Have deep technical expertise in virtualization and containerization technologies (e.g. Kata, Firecracker, gVisor, Sysbox) and are passionate about optimizing runtime performance.
Additional Instructions
Push massive compute clusters to their limits. You will be a core contributor to a novel container orchestration platform built in-house by our team to scale far beyond what’s possible with systems like Kubernetes.
Develop and maintain FastAPI and gRPC APIs that serve as the interface for our agentic infrastructure used both in training and production.
Use Terraform to stand up and evolve complex infrastructure for both research and production.
Collaborate with research teams to stand up and optimize systems for novel AI training runs and experimental applications.
