Infrastructure Engineer — Research Compute & AI

Hikarosquantlab

Greater London

Híbrido

GBP 60.000 - 90.000

Jornada completa

14 días+

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Descripción de la vacante

Hikaros Quant Lab (HQL) is building a quantitative research and technology organisation focused on solving difficult problems in financial markets through mathematics, machine learning and large-scale computing. We are looking for an Infrastructure Engineer to design and operate the computational foundations that enable our researchers and engineers to develop, test and deploy ideas.

This early-stage role offers significant ownership: you will build scalable, reliable systems, manage workloads,

Formación

  • Strong Linux and systems engineering experience.
  • Programming or scripting skills.
  • Experience with cloud, on‑premise or HPC infrastructure.
  • Infrastructure automation / Infrastructure as Code.
  • Strong problem‑solving ability.

Responsabilidades

  • Design and build scalable research and compute infrastructure.
  • Manage CPU/GPU workloads and large-scale computational environments.
  • Build automation, deployment and Infrastructure-as-Code tooling.
  • Develop reliable systems for data, compute and research workloads.
  • Improve performance, observability, security and reliability.
  • Work closely with researchers and engineers to enable rapid experimentation.

Conocimientos

Linux proficiency, systems engineering
Programming/scripting
Cloud/On-prem HPC infra
Infrastructure as Code
Problem solving

Herramientas

Kubernetes
Docker
AWS
GCP

Descripción del empleo

Hikaros Quant Lab (HQL) is building a quantitative research and technology organisation focused on solving difficult problems in financial markets through mathematics, machine learning and large-scale computing. We are looking for an Infrastructure Engineer to design and operate the computational foundations that enable our researchers and engineers to develop, test and deploy ideas.

This early-stage role offers significant ownership: you will build scalable, reliable systems, manage workloads,

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