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Publié il y a 7 jours

Device Platform Engineer(Robotics/GPU Integration) - Vancouver, BC (Onsite) - FTE/perm

@ Harvey Nash

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Vancouver, Colombie-Britannique

Temps plein3+ ans d’expérience
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SIGNAUX

En bref

Harvey Nash is hiring a Software Development Engineer for Device Platform in Vancouver, BC, on a full-time permanent onsite basis. The role builds and maintains low-level platform software for vision-guided robotic systems, bridging hardware and software and automating deployments. The posting states a salary of CAD 125K to 140K per year with benefits.

Responsabilités :

  • Écrire des outils de plateforme en Python et C++ pour automatiser le déploiement
  • Intégrer, conteneuriser et valider les composants matériels
  • Construire l'automatisation Linux avec Ubuntu auto-install et cloud-init
  • Mettre en place des contrôles de santé et des mécanismes de sauvegarde

Résumé des exigences :

  • 3 ans et plus en ingénierie de plateforme ou systèmes
  • Solide maîtrise de Python et C++
  • Expérience approfondie de Linux (Ubuntu) et Docker
  • Expérience d'intégration de composants physiques

Outils et compétences

DockerUbuntucloud-initNVIDIA GPUPythonC++
Source et dates

Type de source non vérifié · apify-linkedin

Date publiée par l’employeur
2026-11-03
Première détection par notre source
2026-11-10
Mise à jour du dossier source
2026-11-10

Ces dates décrivent le dossier source, pas une vérification en direct du recrutement. Consultez l’offre originale.

Détails du poste

NiveauIntermédiaire
DomaineDéveloppement logiciel
Expérience3 an(s) et plus
Heures par semaine40 (estimé)
Milieu de travailBureau, Usine
PositionAssis et debout
Exigences physiquesphysique faible · ordinateur élevé
LanguesEnglish

Résumé et détails rédigés par l’IA à partir de l’offre; l’offre de l’employeur fait foi.

Postuler

Harvey Nash

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ChampValeur
Offres sur Jobsy2
Description

Job Title: Software Development Engineer – Device Platform Engineer

Location: Vancouver, BC (Onsite)

Duration: FTE/Perm

A reasonable, good faith estimate of the minimum and maximum for this position is CAD125K/year to CAD140K/year with benefits

Job Description:

About the Job

Build and maintain the core platform software that powers vision-guided robotic systems. This is a low-level systems engineering role—not web or app development—focused on bridging hardware and software, automating deployments, and ensuring high uptime from the lab to the factory floor.

Key Responsibilities

  • Platform Architecture: Write platform tools in Python and C++ to automate system deployment, provisioning, upgrades, and backups across distributed robots.
  • Hardware Integration: Connect, containerize (via Docker), and validate hardware components, including vision cameras, NVIDIA GPUs, network devices, and robot controllers.
  • Linux Configuration: Build and manage OS-level automation using Ubuntu auto-install, cloud-init, and custom image creation for rapid scaling.
  • Reliability & Uptime: Build automated health checks, self-healing workflows, and backup/restore mechanisms to minimize downtime.
  • Tooling & Optimization: Create internal tools that reduce setup time by 30%+, utilizing AI-assisted diagnostics and performance profiling.
  • Collaboration: Partner with robotics, computer vision, and infrastructure teams across the full technology stack.

Requirements

  • Experience: 3+ years in platform engineering, systems programming, or infrastructure-level software development.
  • Programming: Strong proficiency in Python and C++.
  • OS & Containers: Deep hands-on experience with Linux (Ubuntu), system imaging/provisioning tools (cloud-init, auto-install), and Docker.
  • Hardware Interfacing: Proven experience integrating physical components (GPUs, cameras, controllers, network devices) with software layers.
  • Operations: Solid foundation in DevOps practices, CI/CD pipelines, and automated system testing.

Preferred Qualifications

  • Hands-on work with NVIDIA GPU acceleration inside Docker containers.
  • Experience with industrial camera interfaces, Power over Ethernet (PoE), and network peripheral configurations.
  • Advanced Linux systems knowledge: SELinux, OverlayFS/SquashFS, and kernel/performance profiling tools.
  • Familiarity with AWS cloud infrastructure and distributed architecture.
  • Interest in deploying predictive maintenance and AI-driven monitoring systems.

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