Postuler

Publié il y a 2 mois

Machine Learning Engineer

@ Invision AI

Toronto, Ontario

HybrideTemps plein
Postuler
SIGNAUX

En bref

Invision AI is hiring a full-time Machine Learning Engineer in Toronto to build, ship and maintain computer vision models for intelligent infrastructure and transportation products. The role covers the full ML lifecycle on edge devices, works from the downtown office three days a week, and includes equity, RRSP, health and dental benefits and four weeks of holiday.

Responsabilités :

  • Develop, evaluate and deploy ML models across product lines
  • Build data-labeling, training and evaluation pipelines
  • Optimize models for latency, memory and power on edge devices
  • Monitor production models for drift and retraining needs

Résumé des exigences :

  • Track record of developing and deploying production computer vision models
  • Strong Python and PyTorch, TensorFlow or scikit-learn skills
  • Experience optimizing models for resource-constrained environments
  • Must be legally entitled to work in Canada

Outils et compétences

Avantages mentionnés

Soins dentairesRégime de retraite
Source et dates

Site carrière / système de candidatures · workable

Date publiée par l’employeur
2026-08-28
Première détection par notre source
2026-10-11
Mise à jour du dossier source
2026-10-11

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

Détails du poste

DomaineDonnées et analytique
Heures par semaine40 (estimé)
Milieu de travailBureau
PositionSurtout assis
Exigences physiquesphysique faible · ordinateur élevé
LanguesEnglish
Avantages mentionnésRégime de retraite, Actions ou participation

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

Invision AI

Profil d’entreprise sauvegardé

Renseignements historiques provenant d’un profil The Jobs API sauvegardé (champs LinkedIn/Crunchbase). Ils ne sont pas vérifiés en temps réel; les chiffres peuvent avoir changé. Les valeurs manquantes restent inconnues.

See And Understand The World

Description complète de l’entreprise

Massive amounts of data being created at the edge, uploading this data to the cloud for real-time analysis is neither financially nor technically feasible. Extracting meaning from this data is computationally intensive and expensive, limiting adoption of edge AI to a few high-value applications. After years of research by leaders in computer vision and machine learning we have developed technology that is two to three orders of magnitude more efficient than other high-accuracy deep learning systems. Our patent pending technology evolves the state of the art with a combination of optimization, sprinkled with unique insight and just a little magic. Video is our first application: the system is trained in the cloud by ingesting video where objects and activities of interest have been annotated. Learning is distilled into ultra-efficient software that runs on fixed, body-mounted and vehicle-mounted cameras. We can enable analytics on most professional IP video cameras with just a firmware update. Older cameras can be retrofitted with a low-power embedded processor, such as those from our partners NXP and Ambarella. Our software-only system gets smarter over time: edge cases (where the system is not very confident that it knows what is happening) are captured, uploaded to the cloud for analysis, and the learning distilled into ever smarter software. We work with more than just video: infrared, thermal, radar and lidar play important complimentary roles in helping to establish accurate, detailed situational awareness across a wide variety of environmental conditions. Each sensor detects, classifies and tracks multiple objects locally in real-time. This metadata is then push to the cloud, or a central ECU in the case of a vehicle, where it is fused to establish ground truth, detect behavior, track objects across multiple sensors, and identify anomalies.

Abonnés LinkedIn
5 480
Personnes associées sur LinkedIn
13
Bureaux déclarés
  • 2 Carlton St, Unit 1510, Toronto, Ontario M5B 1J3, CA
  • Rue de Lausanne 64, c/o Fondation Inartis, Renens, Vaud 1020, CH
  • 13140 W Star Dr, Shelby Township, Michigan 48315, US
Catégories d’activité
  • Facial Recognition
  • Artificial Intelligence
  • Software
  • Enterprise Software
  • Internet of Things
  • Artificial Intelligence (AI)
  • Computer Vision
  • Autonomous Vehicles
  • Machine Learning
Autres noms enregistrés
  • Invision AI
Spécialités
  • artificial intelligence
  • machine learning
  • computer vision
  • autonomous vehicles
  • IoT
  • embedded systems
  • smart cameras
  • sensor fusion
  • autonomous vehicles
  • intelligent transportation systems
  • traffic management
  • deep learning
  • edge AI
  • and embedded systems
Le profil indique une agence de recrutement
Non
Investissement total déclaré
1 220 000

La devise et la date d’observation ne sont pas fournies; ce n’est ni une valorisation actuelle ni une ronde de financement.

Massive amounts of data being created at the edge, uploading this data to the cloud for real-time analysis is neither financially nor technically feasible. Extracting meaning from this data is computationally intensive and expensive, limiting adoption of edge AI to a few high-value applications. After years of research by leaders in computer vision and machine learning we have developed technology that is two to…

ChampValeur
SecteurSoftware Development
Taille11-50 employees
Siège socialToronto, Ontario
Type d’organisationPrivately Held
Fondée en2017
Spécialitésartificial intelligencemachine learningcomputer visionautonomous vehiclesIoTembedded systemssmart camerassensor fusionautonomous vehiclesintelligent transportation systems
Offres sur Jobsy8
LinkedInVoir la page
Description

We are looking for a Machine Learning Engineer to join our Toronto team and help us take our products to the next level in terms of visual intelligence.

Our Company

Invision AI is building a universal AI platform for computer vision applications. Powered by a unique multi-camera stack that generates high-integrity 3D digital twins of dynamic environments, our technology powers disruptive, market-leading solutions in intelligent infrastructure and global Transportation.

The Role

As a Machine Learning Engineer, you will work across the full machine learning lifecycle, from data collection and labeling strategy through training, evaluation, deployment, monitoring, and ongoing improvement.

Your focus will be developing and maintaining computer vision models used in real-world products. While the work may involve researching and implementing new approaches, this is primarily an applied engineering position. We are looking for someone with a track record of building, shipping, and maintaining production ML systems.

The position includes working on projects that expand and strengthen our capabilities in object detection, image classification, geospatial tracking, and sensor fusion, with models deployed to resource-constrained edge devices.

Working within a collaborative team, you will build accurate, efficient, and principled solutions. As a key contributor to the company's next stage of growth, you will help advance our products, solve challenging customer problems, and shape our ML engineering practices in a fast-moving environment.

Location

This is a full-time, hybrid position based in Toronto. You will work from our downtown Toronto office three days per week.

What You'll Do

  • Recommend, develop, evaluate, and deploy ML models across our product lines
  • Build and improve data-labeling, training, and evaluation pipelines
  • Establish evaluation methods that connect model performance to product and business outcomes
  • Prototype new product capabilities using appropriate technologies
  • Optimize models for latency, memory usage, power consumption, and accuracy on edge devices
  • Diagnose and resolve issues affecting deployed models
  • Monitor production performance and identify model drift, data-quality problems, and retraining needs
  • Write maintainable, well-tested code and clear technical documentation
  • Participate in design reviews, code reviews, and technical planning
  • Share ML knowledge and collaborate with software, product, and other engineering teams

Must Have

  • A track record of developing and deploying production computer vision models
  • Strong Python software development skills
  • Proficiency with frameworks such as PyTorch, TensorFlow and scikit-learn
  • Practical knowledge of CNNs and modern computer vision architectures
  • The ability to adapt open-source models to specific products and use cases
  • Hands-on work optimizing models for resource-constrained or edge environments
  • Knowledge of experiment tracking, dataset versioning, and ML observability
  • Skill in designing evaluation metrics that reflect product and business requirements
  • An understanding of model monitoring and production troubleshooting
  • Working knowledge of embedded systems and their constraints
  • Sound software engineering practices, including automated testing, code review, version control, and continuous integration
  • Strong written and verbal communication skills
  • Must be legally entitled to work in Canada

Bonus Skills

  • Familiarity with Docker or other container technologies
  • C++ development skills
  • GPU programming or performance-optimization knowledge
  • Knowledge of model compression techniques, including quantization, pruning, and knowledge distillation
  • Familiarity with edge inference tools such as ONNX Runtime, TensorRT
  • Familiarity with traditional, non-ML image-processing techniques
  • A background in sensor fusion or geospatial data
  • A Mission that Matters: The opportunity to work on projects that make the world safer and greener
  • Excellence: A culture of very high technical standards where quality engineering is valued over quick hacks
  • Technical Challenge: A wide variety of technology and tasks, including web development, distributed and edge computing, ML, real-time processing, and computer vision
  • Growth Environment: Join an international team where your voice is heard and your impact is visible
  • Compensation and benefits: Competitive salary package including equity, allowing you to share in the success you help build. Benefits: RRSP Plan, Health and Dental and 4 weeks holiday.

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