Remote: Technical Lead, GPU Infra & HPC Platform

Jobgether; Canada; Remote; CAD 150,000 - 230,000; Full time

Benefits offered by this job

100% remote position

Lead architecture and delivery of GPU/

International and distributed team

Job summary

Jobgether in Canada is seeking a Technical Lead for GPU Infrastructure to architect and deliver a large-scale GPU platform. You will guide a distributed team across backend, frontend, DevOps, QA, and documentation, taking ownership of design and delivery for research, model training, and managed inference workloads.

You will oversee bare-metal GPU environments, Slurm, and Kubernetes, with focus on reliability, observability, and capacity planning.

Qualifications

• 8+ years engineering experience with at least 3 years leading infra teams.
• Bachelor's or Master's degree in CS/Engineering or equivalent practical experience.
• Hands-on production HPC/GPU cluster experience.
• Strong Linux systems, kernel, and performance tuning expertise.
• Excellent written and spoken English and cross‑functional collaboration skills.

Responsibilities

• Own the platform architecture and engineering delivery for GPU infrastructure.
• Lead a distributed engineering team across backend, frontend, DevOps, QA, and documentation.
• Design, build, and operate a Slurm service supporting research workloads and model training.
• Maintain high technical standards through reviews, release gates, and on‑call readiness.
• Partner with vendors and internal teams to translate workloads into platform requirements.

Skills

GPU infrastructure

Slurm

Kubernetes

Linux systems

NVIDIA GPUs (bare metal)

Observability

Team leadership

JavaScript / Node.js

Architecture design

Cloud-native / IaC / GitOps

Performance tuning

Education

Bachelor's or Master's in CS/Engineering or equivalent

Tools

Slurm

Kubernetes

NVIDIA Driver

Fabric Manager

NVSwitch

DCGM

KubeVirt

VFIO

Job description

Jobgether in Canada is seeking a Technical Lead for GPU Infrastructure to architect and deliver a large-scale GPU platform. You will guide a distributed team across backend, frontend, DevOps, QA, and documentation, taking ownership of design and delivery for research, model training, and managed inference workloads.

You will oversee bare-metal GPU environments, Slurm, and Kubernetes, with focus on reliability, observability, and capacity planning.