Posted 7 days ago
Device Platform Engineer(Robotics/GPU Integration) - Vancouver, BC (Onsite) - FTE/perm
@ Harvey Nash
Vancouver, British Columbia
Overview
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.
Responsibilities:
- 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
Requirements summary:
- 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
Tools & skills
Source and dates
Source type not verified · apify-linkedin
- Employer posting date
- 2026-11-03
- First seen by our source
- 2026-11-10
- Source record updated
- 2026-11-10
These dates describe the source record, not a live verification that the employer is still hiring. Check the original posting.
Job details
| Seniority | Mid level |
| Department | Software development |
| Experience | 3+ years |
| Hours per week | 40 (estimated) |
| Work setting | Office, Plant or factory |
| Position | Sitting and standing |
| Physical demands | physical low · computer high |
| Languages | English |
Summary and details written by AI from the posting; the employer’s posting is the authority.
Harvey Nash
| Field | Value |
|---|---|
| Open jobs on Jobsy | 1 |
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.
Journal
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