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9 часов назад

Backend and Infrastructure Engineer (AI)

165 000 - 180 000$
Формат работы
hybrid
Тип работы
fulltime
Грейд
senior
Английский
b2
Страна
US
Вакансия из списка Hirify.GlobalВакансия из Hirify Global, списка международных tech-компаний
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Описание вакансии

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TL;DR
Backend and Infrastructure Engineer (AI) (Python/C++/Terraform): Building and operating backend services and cloud infrastructure for a production-scale physics simulation and inference platform with an accent on reproducible builds, automated pipelines, and scalable deployment. Focus on provisioning infrastructure with Terraform, hardening CI/CD and build systems, and taking research prototypes through production for billion-voxel workloads.

Location: Palo Alto, United States; hybrid

Salary: $165K–$180K per year

Company

hirify.global is an early-stage AI startup building operator intelligence infrastructure for semiconductor and hardware companies, including production-scale physics simulation and inference systems.

What you will do

  • Design, build, and operate backend services and infrastructure for the simulation and inference platform.
  • Own Terraform infrastructure-as-code across cloud environments.
  • Build and harden CI/CD pipelines with Jenkins or an equivalent system.
  • Maintain build systems for large Python and C++ codebases using CMake and pip/uv.
  • Take early research prototypes through iterative hardening and customer-ready production deployment.
  • Partner with physicists, AI researchers, software engineers, and computational geometry experts to turn research into dependable systems.

Requirements

  • 8+ years of professional software engineering experience focused on backend and infrastructure.
  • Hands-on Terraform experience and production experience with a major cloud platform such as GCP, AWS, or Azure.
  • Experience building and maintaining Jenkins or equivalent CI/CD pipelines.
  • Proficiency in Python and working familiarity with C++.
  • Comfort with CMake, Python packaging via pip/uv, and large multi-language codebases.
  • Experience contributing to a production data-processing or platform system, with strong software engineering, regression testing, and validation practices.

Nice to have

  • Experience taking an early-stage prototype to production at a startup or national lab.
  • Experience with ML or scientific-computing workloads, including PyTorch, NumPy, CUDA, or GPU infrastructure.
  • Experience with Docker, Kubernetes, observability tooling, frontend development, or 3D rendering and visualization.

Culture & Benefits

  • Work in a small, accessible team with significant ownership and autonomy.
  • Architect foundational platform components alongside physicists, AI researchers, software engineers, and computational geometry experts.
  • Contribute to greenfield development and scale infrastructure supporting Tier-1 semiconductor and hardware customers.
  • Help accelerate physics-based design validation from hours to seconds while maintaining solver-grade accuracy.

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