Назад
11 часов назад

AI Infrastructure Engineer (LLM Serving)

Формат работы
onsite
Тип работы
fulltime
Грейд
senior
Английский
b2
Страна
UK
Вакансия из списка Hirify.GlobalВакансия из Hirify Global, списка международных tech-компаний
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Описание вакансии

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TL;DR

AI Infrastructure Engineer (LLM Serving): Designing and building platforms for scalable, reliable, and efficient serving of LLMs with an accent on backend system design and infrastructure scalability. Focus on building fault-tolerant systems, optimizing model routing, and implementing observability for large-scale AI production environments.

Location: London, UK

Company

Scale AI provides high-quality data and full-stack technologies that power the world's leading AI models for enterprises and governments.

What you will do

  • Build and maintain fault-tolerant, high-performance systems for serving LLMs and other models at scale.
  • Develop an internal platform to empower LLM capability discovery.
  • Collaborate with researchers and engineers to integrate and optimize models for production and research use cases.
  • Conduct architecture and design reviews to ensure best practices in system design and scalability.
  • Develop monitoring and observability solutions to ensure system health and performance.
  • Lead end-to-end projects from requirements gathering to implementation in a cross-functional environment.

Requirements

  • 4+ years of experience building large-scale, high-performance backend systems.
  • Strong programming skills in Python, Go, Rust, or C++.
  • Experience with LLM serving and routing fundamentals such as rate limiting, token streaming, and load balancing.
  • Understanding of LLM concepts including reasoning, tool calling, and prompt templates.
  • Experience with containers and orchestration tools like Docker and Kubernetes.
  • Familiarity with cloud infrastructure (AWS, GCP) and Infrastructure as Code (Terraform).

Nice to have

  • Experience with modern LLM serving frameworks such as vLLM, SGLang, TensorRT-LLM, or text-generation-inference.

Culture & Benefits

  • Inclusive and equal opportunity workplace committed to diversity.
  • Collaborative environment bridging the gap between AI research and engineering.
  • Provision of reasonable accommodations for applicants with physical and mental disabilities.

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