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2 months ago

Fullstack AI Platform Engineer (Python, Rust, Kubernetes)

Work format
hybrid
Work type
fulltime
English
b2
Country
US
This vacancy is from Hirify.Global listVacancy from Hirify Global, list of international tech companies
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Job description

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TL;DR
Fullstack AI Platform Engineer (Python, Rust, Kubernetes): Build and evolve an AI platform that unifies compute, environments, evaluations, secure sandboxes, training, and deployment with an accent on backend feature development, distributed training infrastructure, and high-performance observability. Focus on designing REST APIs and real-time monitoring, implementing Rust-based systems for distributed training and networking, and automating cloud/container operations for heterogeneous GPU/CPU/TPU scheduling.

Location: San Francisco

Company

hirify.global builds an open superintelligence stack and an AI platform for frontier-scale post-training and deployment.

What you will do

  • Build web interfaces for AI workload management, monitoring, and resource/job control.
  • Develop REST APIs and backend services in Python to support new platform capabilities.
  • Create real-time monitoring and debugging tools for platform operations.
  • Design and implement distributed training infrastructure in Rust, including high-performance networking and coordination components.
  • Build infrastructure automation pipelines with Ansible and manage cloud resources and container orchestration.
  • Implement scheduling systems for heterogeneous hardware (CPU, GPU, TPU) and integrate new features into existing infrastructure with reliability and security.

Requirements

  • Strong Python backend development (FastAPI, async) and RESTful API design/implementation.
  • Modern frontend development experience (TypeScript, React/Next.js, Tailwind) and building developer tools/dashboards.
  • Systems programming experience with Rust.
  • Infrastructure automation experience (Ansible, Terraform) and container orchestration with Kubernetes.
  • Observability experience with Prometheus and Grafana.
  • Experience with GPU computing and ML infrastructure, including knowledge of AI/ML model architecture and training.

Culture & Benefits

  • Hybrid role combining AI platform software engineering and infrastructure work.
  • Open development culture with encouragement to contribute to the broader AI community via research and open-source.
  • Focus on potential over perfection.
  • Work at the intersection of frontier research, real infrastructure, and go-to-market for an emerging category.

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