Postuler

Publié il y a 14 jours

Edge/Systems Engineer

@ TAIRC

Niagara-on-the-Lake, Ontario

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SIGNAUX

En bref

TAIRC is recruiting a volunteer Edge/Systems Engineer in its Applied AI Engineering department to optimize AI models for mobile and edge devices. The role covers embedded systems, hardware accelerators, on-device inference, and securing data and models on devices. The posting describes this as a volunteer contribution with no compensation at this stage.

Responsabilités :

  • Develop edge inference systems and optimize models for mobile and edge devices
  • Collaborate with device manufacturers on efficient inference solutions
  • Design systems for limited memory and compute
  • Implement security measures to protect data and models on devices

Résumé des exigences :

  • Bachelor's or master's degree in electrical or computer engineering
  • Experience with embedded systems
  • Experience with hardware accelerators
  • Experience with on-device inference

Outils et compétences

Source et dates

Type de source non vérifié · apify-linkedin

Date publiée par l’employeur
2026-10-30
Première détection par notre source
2026-11-14
Mise à jour du dossier source
2026-11-14

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

Détails du poste

DomaineGénie
Milieu de travailBureau, Laboratoire
PositionSurtout assis
Exigences physiquesphysique faible · ordinateur élevé
FormationBaccalauréat (exigé), Maîtrise (exigé)
Domaines d’étudesElectrical engineering, Computer engineering

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

ChampValeur
Offres sur Jobsy1
Description
Home/Careers/Edge/Systems Engineer

Applied AI Engineering

Edge/Systems Engineer

These engineers focus on resource-constrained deployments such as edge devices and embedded systems.

Apply for this roleManage an applicationBack to careers

Overview

These engineers focus on resource-constrained deployments such as edge devices and embedded systems.

Responsibilities

  • Develop edge inference systems: Optimize models for mobile and edge devices.
  • Collaborate with hardware teams: Work with device manufacturers to implement efficient inference solutions.
  • Ensure reliability in constrained environments: Design systems for limited memory and compute.
  • Implement security measures: Protect sensitive data and models on devices.

Qualifications

  • Bachelor's or master's degree in electrical engineering or computer engineering.
  • Experience with embedded systems, hardware accelerators, and on-device inference.

Equal opportunity

TAIRC evaluates candidates using role-related evidence and documented review criteria. Employment decisions must not be based on protected personal characteristics.

Engagement pathways and compensation status

TAIRC is currently building its funding base. Opportunities identified as volunteer or unpaid do not provide compensation at this stage. Any future paid appointment would require available funding, organizational approval, applicable legal compliance, and a separate written agreement. Participation does not guarantee future employment or compensation.

  • Volunteer contribution interest may be reviewed only as a voluntary, scoped pathway.
  • Educational internship interest requires separate supervision, educational purpose, and legal review.
  • Advisory expressions of interest are not board or formal advisory appointments.
  • Future compensated employment is contingent on funding, approval, legal compliance, and a separate written offer.

Accessibility and accommodations

For an accommodation or alternate submission format, contact [email protected]. The application form does not request medical documentation or sensitive identity documents.

Posting information

Department Applied AI Engineering

Public role ID TAIRC-ROLE-021

Status Open

Location, employment type, workplace type, compensation, sponsorship policy, posted date, and closing date are omitted unless HR has entered approved factual values.

Recruitment privacy

Application data is used for recruitment review, stored with restricted access, and handled under the recruitment privacy and retention policy.

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